Page 21 – DataToBiz

Yashica Chopra
September 18, 2023
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Step-By-Step Guide to Digital Transformation

Digital transformation has been a part of the global industry for years. However, it was considered a tool to have a competitive advantage in the pre-Covid era. Now the digital transformation is a must for every business, a startup, or an established multinational company. Statistics show that the global digital transformation market is expected to grow at a CAGR (Compound Annual Growth Rate) of 16.5% from 2020 to 2025 to touch $1009.8 billion. The World Economic Forum said the digital transformation will add $100 trillion to the global economy by 2025, with interactive platforms taking up two-thirds of the total value. Similarly, data from Statista show that the global investment in digital transformation will grow from $1.8 trillion in 2022 to $2.8 trillion by 2025. With everyone around the world talking about digitally transforming their businesses, it’s vital to understand what it actually means and how to implement the process correctly. Here’s a step-by-step guide to digital transformation with answers to questions like who should lead digital transformation and what is the fundamental meaning of digital transformation? What is Digital Transformation? Digital transformation is the process of establishing a digital-first approach in a business to streamline internal processes, revamp business models, enhance customer experience, and increase ROI. Advanced technologies like artificial intelligence, hybrid cloud, automation, machine learning, etc., are used to leverage data, create seamless data flow, and empower smarter decision-making. It offers a real-time solution to market disruptions and creates new business opportunities for growth and success. Digital transformation is not a one-time fix. It is the continuous adoption of technologies to deal with changing market conditions and customer requirements in the best possible manner. So do you need a vision for a digital transformation agenda? Absolutely! How you digitally transform your business depends on various factors, such as your organization’s vision, mission, goals, target market, etc. To create a robust and comprehensive digital transformation agenda or strategy for your business, you should first understand what is crucial for the enterprise and how it can be achieved. Hiring a digital transformation service provider or consulting company is a stress-free method to handle the process effectively. Digital Transformation Strategy Every enterprise has its own strategy to digitally transform its processes and systems. There is no single methodology that suits all businesses. But how do you determine your optimal digital transformation strategy? It’s done by aligning the digital transformation strategy with the organization’s strategy and following the two most important principles: Defining and detailing the strategy will provide a clear picture and make it easy to implement digital transformation in the business. Digital Transformation Technologies While any digital technology can be used to transform business processes, some technologies have a central role and are a must for every enterprise. However, digital transformation will be successful when you know which technology is the best for your needs. Consulting companies not only help choose the right tools and technologies but also customize and integrate them with the business systems to increase overall efficiency and performance. The top digital transformation technologies are: Building Blocks of Digital Transformation The building blocks of digital transformation can be varied and extensive, depending on the enterprise’s requirements. Nevertheless, these are broadly classified into four major categories: Digital transformation in organizations begins with identifying the elements under each building block. Having a detailed, high-level checklist will ensure you don’t miss any crucial factors when adopting the latest technologies and processes in your enterprise. Digital Strategy You should ask three major questions when setting the strategy- With ever-changing answers, you should make sure the digital strategy has components that support making proactive business decisions in the present and future. Identifying the stepping stones and challenges helps choose the right areas to implement the changes. A Gartner report shows that 60% of mainstream enterprises mention that becoming a composable business is their strategic objective to outperform their competitors and implement new developments 80% faster. Business Model The ultimate goal of business digital transformation is to drive real value for customers through improved business operations. It should bring greater ROI and help enterprises achieve their desired outcomes. Hence, this category contains components like operations, business economic model, products & services, and customer & engagement across the selected channels. The primary intent is to find ways to derive additional value from the improvements without increasing the costs. Enablers As the term suggests, enablers are the tools, technologies, and methodologies that help achieve the goals and initiate digital transformation in the enterprise. It also includes people (internal and external) who play varied roles in using technology and achieving success. However, the biggest challenge lies in building an in-house team and encouraging existing employees to adopt digital transformation. The most prominent enablers of digital transformation are: Many organizations partner with offshore service providers to save hiring costs and the time taken to build a team from scratch. Consulting companies also assist and train existing employees to become comfortable with new technology and use it effectively to increase their performance at work. Orchestration The final and crucial building block of digital transformation is orchestration, or the process of how to get it done. It deals with finding investors, creating a fund, setting governance regulations, scaling the systems, identifying competent leaders, and promoting community engagement to involve everyone in the process. Many challenges arise in this stage and determine the end results of digital transformation in a business. For example, a wrong leader could put the entire organization at risk. Partnering with digital transformation consulting companies reduces risks and empowers your business at various levels. Guide to Digital Transformation Your digital transformation approach has to be structured in a systematic process to prevent mistakes and unexpected roadblocks. Be it a small business or a large enterprise, planning and implementing digital transformation is no small feat. The process is extensive and requires time, money, resources, expertise, and dedication. Here’s a step-by-step guide to implementing digital transformation in your enterprise: 1. Define Your Vision Firstly, define what you want to achieve by implementing your digital transformation ideas. The vision changes from one business to another, even

Manpreet Kaur
September 15, 2023
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Business Intelligence In Real Estate: Empowering Industry with Insights

Business intelligence empowers real estate with valuable insights and informed decision-making by streamlining property search, enhancing listings,and simplifying buying and selling processes. Utilizing business intelligence in the real estate industry can offer significant advantages due to the vast potential of the market. The global real estate market size was valued at USD 3.69 trillion in 2021 and is expected to expand at a compound annual growth rate (CAGR) of 5.2% from 2022 to 2030. The implementation of business intelligence tools in the real estate sector enables investors to optimize profits and overcome obstacles. Many sectors, including finance, healthcare, transportation, and logistics, recognize the value of investing in business intelligence software development to unlock their business’s growth potential. Therefore, it is crucial to explore the benefits of business intelligence for real estate businesses. Can a real estate business intelligence solution deliver these advantages? In this article, we will outline the benefits of implementing business intelligence in the real estate industry, highlighting the five styles of business intelligence. Understanding Business Intelligence in Real Estate ● Business intelligence in real estate involves the collection, analysis, and interpretation of vast amounts of data to gain valuable insights and make informed decisions. ● Key components of BI in real estate include data gathering, storage, integration, analysis, and reporting. ● By harnessing the power of technology, including data visualization tools and predictive analytics, BI enables real estate professionals to extract actionable intelligence from complex data sets. What is Market Intelligence in Real Estate? Market intelligence in real estate refers to the process of gathering and analyzing data to understand market dynamics, trends, and opportunities. It involves monitoring and evaluating factors such as property values, rental rates, vacancy rates, supply and demand, economic indicators, and demographic information. Market intelligence provides a comprehensive view of the real estate market, enabling stakeholders to identify potential investment opportunities, predict market trends, and make strategic decisions. How is business intelligence used in real estate? The real estate industry is characterized by its complexity, involving large-scale operations with intricate details. In this context, data plays a crucial role. However, sifting through vast amounts of information can be a challenging task. This is where real estate business intelligence software becomes invaluable. A customized business intelligence solution tailored for the real estate industry not only analyses the extensive data generated from smart tools and systems but also helps identify key performance indicators (KPIs) for your organization. Additionally, commercial real estate can leverage bespoke BI solutions to explore new revenue models. When combined with machine learning algorithms, real estate business intelligence software provides actionable insights that assist investors in effectively managing their portfolios. Without a robust data interpretation system in place, valuable information and insights may go unnoticed, resulting in missed opportunities. However, by effectively reading and interpreting data, businesses can make informed decisions, leading to higher return on investment (ROI) and reduced costs. As you strive to optimize and grow your real estate business more efficiently, leveraging business intelligence and data analytics can be immensely beneficial. It is well-established that real estate heavily relies on business intelligence software solutions, as they offer significant advantages to companies, sellers, investors, and homebuyers alike. What are the benefits of business intelligence in real estate? Business intelligence offers numerous benefits in the real estate industry, revolutionizing various aspects of the business: Streamlined property search Business intelligence tools simplify the process of searching for properties. Users can analyze real estate data quickly, compare options, and make informed decisions. BI tools provide insights into nearby properties, allowing users to explore alternatives conveniently. Enhanced property listings Real estate platforms incorporating business intelligence software improve property listings. Sellers and brokers can provide detailed information about properties, helping potential buyers make informed purchase decisions. BI tools also utilise user search history and preferences to personalize property recommendations and create tailored offers. Efficient selling process Business intelligence software benefits both sellers and brokers. By analyzing past market performance and sales data, BI tools help sellers set competitive asking prices and stay updated with market trends. This streamlines the selling process and maximises profitability. Additionally, it eliminates the need for hiring additional staff to handle market analysis. Simplified property buying BI software simplifies the property buying process by offering tracking features. Users can monitor industry performance, such as property sales in specific locations, facilitating the setting of competitive prices. Business intelligence tools also provide insights and trends, leading to more closed deals and effective marketing strategies. Moreover, they offer a cost-effective alternative to hiring resources for data analysis. Financial management BI software in real estate enables efficient financial management. Instead of relying on complex reporting processes, real-time financial data is visualised on a dashboard. This allows users to monitor balance and cash flow statements and perform analysis and forecasting techniques easily. Connecting financial data with core business data provides comprehensive insights. Informed decision making Real estate business intelligence software empowers decision-making by consolidating data from various sources. The software provides valuable insights into all segments of the business, enabling profitable goal-setting and informed decision-making. By combining data sources, BI tools offer a comprehensive view of the business’s performance. Accurate pricing Business intelligence integrated software assists in setting the right asking price for properties. Whether you are a seller or buyer, analyzing trends provided by BI tools helps determine competitive and effective pricing strategies, leading to successful sales. Faster deal closure Business intelligence software expedites the deal closure process. In commercial real estate, where time is critical, BI tools provide access to comprehensive and up-to-date data. This allows brokers to identify and capitalise on profitable opportunities quickly. Visual representations like graphs and charts facilitate data interpretation, enabling efficient deal identification and closure. Conclusion The real estate industry is experiencing remarkable growth, and companies are actively exploring emerging technologies and innovative solutions to stay ahead. One such powerful tool gaining prominence is business intelligence (BI) in real estate. BI enables businesses to bridge the gap between market understanding and accurate forecasting, empowering them to make informed decisions. It also

Manpreet Kaur
September 09, 2023
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Overcoming Procurement Challenges: Strategies and Solutions

Procurement can be a real nightmare for businesses, from navigating complex regulations to managing multiple suppliers across the globe. One misstep can lead to missed deadlines, poor-quality products, hefty fines, and global supply chain disruption. For instance, The World Economic Forum estimates that disruptions in global supply chains can lead to a loss of $4.4 trillion in global GDP. But before that, let’s first understand what procurement means. What is Procurement? Procurement, the process of acquiring goods and services, is a crucial aspect of any business. It involves selecting suppliers, negotiating contracts, and managing relationships with them to ensure the timely delivery of quality products or services. In today’s business landscape, organizations face a range of procurement challenges that can impact their operations, reputation, and bottom line. In this blog, we will discuss the top procurement challenges and strategies to overcome them. Effective procurement is critical for organizations as it enables them to control costs, manage risks, and maintain a competitive edge. It also plays a vital role in ensuring that organizations comply with regulatory requirements and ethical standards. As such, procurement must be managed efficiently to achieve business goals and objectives. Top Procurement Challenges As organizations strive to stay competitive in today’s ever-changing business landscape. Procurement has become a critical function that can make or break their success. However, there are numerous challenges, that professionals must stay informed about and adapt accordingly, to stay ahead of the game. Supply Chain Transparency Lack of transparency in the supply chain can lead to various issues, including poor-quality products, delivery delays, and reputational damage. It can be challenging to track the movement of goods and services across the supply chain, particularly if there are multiple suppliers involved. Data Management Managing procurement-related data can be complex, particularly if it is spread across different systems or departments. Inaccurate or incomplete data can lead to errors in forecasting, budgeting, and supplier selection. Without accurate and complete data, organizations may struggle to identify cost-saving opportunities, negotiate favorable contracts, and assess supplier performance effectively. Supplier Relationship Management Establishing and maintaining effective supplier relationships is essential for procurement success. However, managing multiple supplier relationships can be challenging, particularly if they are spread across different regions and time zones. This can result in ineffective communication, resulting in process delays and breakdowns. Compliance and Regulatory Issues Organizations must comply with a range of regulatory requirements, such as labor laws, environmental regulations, and data privacy regulations. Non-compliance can lead to hefty fines, reputational damage, and legal issues. Non-compliance with regulatory requirements can result in hefty fines. For instance, in 2020, the US Department of Justice imposed $2.8 billion in fines on companies for violations of the Foreign Corrupt Practices Act. Cost Management Managing costs is a top priority for procurement professionals. However, it can be challenging to balance cost-saving measures with the need to maintain quality and meet delivery deadlines. According to a 2021 Deloitte Global Chief Procurement Officer survey, the top three procurement priorities for businesses are cost optimization, supply chain resilience, and improving operational agility. Risk Management Procurement involves various risks, such as supplier bankruptcy, delivery delays, and quality issues. Failing to manage these risks can lead to operational disruptions and financial losses. Strategies for Overcoming Procurement Challenges Procurement is a critical function in any organization, responsible for sourcing and acquiring the goods and services needed to support the business. Despite these obstacles, procurement teams can overcome them and emerge stronger by adopting effective strategies. Leveraging Technology Solutions A study by the Hackett Group found that procurement organizations that leverage technology to automate processes and improve data quality can achieve up to 25% savings in procurement costs. Technology solutions such as procurement software, e-sourcing platforms, and data analytics tools can help organizations manage procurement more efficiently. These solutions can automate manual processes, streamline workflows, and provide real-time insights into procurement data. Investing in Supplier Relationship Management Programs Developing robust supplier relationship management programs can help organizations build strong and long-lasting relationships with their suppliers. This involves regular communication, performance evaluations, and incentivizing suppliers to meet key performance indicators. Risk Management: Assessment and Planning Regular risk assessments help organizations identify and mitigate procurement-related risks. This involves evaluating the likelihood and potential impact of various risks and developing risk management plans to mitigate them. Improving Compliance Training & Monitoring Organizations should develop comprehensive compliance monitoring and training programs to ensure that employees and suppliers comply with regulatory requirements and ethical standards. This includes regular audits, training sessions, and communication about the importance of compliance. Implementing Cost-Saving Measures Organizations can implement various cost-saving measures, such as consolidating suppliers, negotiating better contracts, and reducing waste. However, it is essential to balance cost-saving measures to maintain quality and meet delivery deadlines. Implementing Solutions for Procurement Challenges Implementing the above strategies can help organizations streamline their operations & gain more visibility above the procurement challenges. However, overcoming these challenges may require assistance from technology and industry experts. It requires more understanding of the business data, risks associated, and regulatory updates. Data Analytics Data analytics companies and business intelligence consultancy services provide organizations with the expertise and tools needed to manage procurement-related data more efficiently. These services help organizations identify patterns, trends, and insights from their procurement data, enabling them to make better-informed decisions. Benefits of Data Analytics Improved Data Quality: Data analytics consultancy services help organizations improve the quality of their procurement-related data. By standardizing and cleansing data, organizations ensure that it is accurate, complete, and up to date. This, in turn, enables organizations to make better-informed decisions, reduce errors, and improve supplier performance. Real-time Insights: Data analytics consultancy services provide organizations with real-time insights into their procurement data. By using dashboards, reports, and other visualization tools, organizations can quickly identify trends, patterns, and anomalies in their procurement data, enabling them to take corrective actions promptly. Cost Savings: Data analytics consultancy services help organizations identify cost-saving opportunities. By analyzing procurement data, organizations can identify areas where they can reduce costs, such as by consolidating

Yashica Chopra
September 07, 2023
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Leveraging Power BI in FMCG

Insights derived from retail and eCommerce data can help the FMCG industry in various ways. Business intelligence tools like Power BI are useful in making faster business decisions based on real-time data. Here, we’ll discuss the role of BI in FMCG markets. FMCG (Fast-Moving Consumer Goods) is also known as Consumer-Packaged Goods and deals with a large variety of perishable and durable goods from different industries. From food items to cosmetics, stationery, and groceries, many products are categorized as FMCG. According to Cognitive Market Research, the global FMCG market is estimated to reach $17,939.41 billion by 2030, with a CAGR (compound annual growth rate) of 6.11%. In other statistics, The FMCG’s share is expected to touch 18% this year in Africa. The FMCG market is always bustling with activity online and offline. Countless sales happen each day around the globe. Needless to say, large volumes of data are generated by businesses, vendors, and customers. This data can be analyzed to make better decisions and streamline internal operations. FMCG Business Intelligence is in high demand in the market to derive data-based analytics and insights. Business intelligence is a part of many industries. The global BI software market is expected to touch US$25.73 billion in 2023. In this blog, we’ll read more about the use of analytics and reporting in the FMCG industry and the role of Power BI in delivering insights in real-time. What is the Role of Analytics in FMCG? Digitization The FMCG industry is going digital by adopting the latest technologies and tools to collect, store, and analyze data generated by businesses. This allows for seamless connectivity, greater flexibility, agility, and scalability. Inventory Management Business intelligence companies create exclusive dashboards to provide data visualizations about inventory held by the business at the manufacturing unit, warehouses, stores, and the ones in transit. This enables brands to cater to the changing market demands without running out of stock. Supply Chain The supply chain is vital for the FMCG industry to thrive. We have seen how disruption affected businesses during Covid lockdowns. However, analytics can help businesses prepare for such adverse conditions and minimize losses. Warehouse Operations A smarter warehouse is more effective and can reduce the risk of damage to the stored items. Using warehouse management software and integrating it with data analytics tools will provide real-time insights about stock levels, shipment movement, etc. Logistics and Transport FMCG analytics and reporting dashboards can help businesses plan their deliveries carefully to avoid delays and increase customer satisfaction. Geo-analytics makes it easier to plan the distribution and delivery routes to minimize cost, distance, and time taken for the shipment to reach from one point to another. Personalization Customers demand personalization in today’s world. Brands can offer personalized products, deals, discounts, and loyalty programs by analyzing customer data to understand their preferences. This will increase customer loyalty and attract more consumers to the business. Pricing and Sales The prices of FMCG products are flexible and change based on market demand, quality, availability, etc. Businesses can adopt a proactive pricing model to automatically adjust the prices based on the insights derived from BI tools. How is Power BI Used in the FMCG industry? Microsoft Power BI is a popular business intelligence tool used by many leading businesses from different industries. Companies hire BI consultants to set up the Power BI dashboards and customize them based on business requirements, goals, and metrics. In this section, we’ll see how the tool can be used in the FMCG industry to deliver real-time insights for decision-making. Unified Analytics The FMCG data comes from various sources like legacy systems, IoT (Internet of Things) devices, packaging units, distribution units, warehouses, factories, stores, etc. This data has to be combined and presented in a single dashboard to streamline the business operations. Power BI is used to create a unified dashboard with real-time data updates from several sources. Decision makers can get a macro and micro view of the data from each source and organize the dashboard layout to suit their needs. Monitor KPIs KPIs or Key Performance Indicators are essential for every business and department to track their progress and ensure they are moving in the right direction. Businesses can build Power BI KPI dashboards to track each indicator/ metric with the goals, resources, and other influencing factors. It allows employees to make proactive decisions to achieve weekly/ monthly/ quarterly/ yearly goals based on real-time data. Sales Dashboard How many sales have each product recorded for the defined duration? What is the overall sales value? How is each store performing in reaching the sales targets? The Microsoft Power BI sales dashboard provides answers to many such questions. It keeps the sales and finance departments up to date with the latest information about the stock. This allows employees to plan and implement marketing campaigns at the right time to boost sales. It also shows the weak areas where the business needs to improve to sell more products. Supply Chain Dashboard The FMCG industry cannot afford supply chain disruptions. Reactionary decisions can help with damage control but don’t minimize risk. However, with a supply chain Power BI dashboard, businesses can track the internal and external factors that can cause trouble. The dashboard provides warning signs and alerts to be proactive in avoiding risk and minimizing losses. It also helps choose the best path to optimize resources and maximize returns. From comparing vendors to speeding up deliveries, the dashboard is helpful in many ways. Campaign Analysis Dashboard Power BI in the FMCG industry also helps in streamlining marketing campaigns and analyzing their performance. Many brands in the industry rely on omnichannel marketing to reach out to a wide range of target audiences. This data from multiple sources can be easily collected and analyzed to provide clear reports using the Power BI tool. It is a great way to work on the Marketing Mix Model, where multiple factors, such as price, promotion, market demand, product placement, etc., are used to determine if the campaign is converting into revenue. Demand Forecasting Dashboard Business intelligence is combined

Yashica Chopra
September 05, 2023
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Top 13 Data Engineering Trends and Predictions 2025

Data engineering is the process of building, deploying, and integrating data pipelines to streamline data flow within an enterprise. It is the foundation for business intelligence processes to run and deliver actionable insights. Here, we’ll discuss the top data engineering trends and predictions for 2025. Data engineering is a growing discipline in the global market. It involves the process of designing and building data pipelines to collect, transform, and transport data to end users (data analysts and data scientists) to derive actionable insights. The data pipelines have to connect all data sources to the central data warehouse or data lake. The success and accuracy of data analytics depend on how well data engineers set up the foundation. This requires high-level data literacy skills. Unfortunately, there is a gap between the demand and supply of qualified and experienced data engineers in the market. It’s one of the primary reasons many SMBs and large enterprises partner with offshore data engineering companies to adopt advanced data-driven technologies and processes for effective decision-making. Many experts feel that 2025 will be a vital year for data engineering. In this blog, we’ll take a detailed look at the various big data engineering trends and predictions that will transform the industry at different levels. 13 Top Data Engineering Trends and Predictions in 2025 1. Increase in Cloud Management Cloud has become a favorite for many businesses around the world. Small, medium, and multinational companies are moving their data and IT infrastructure from on-premises to cloud servers. Data Engineering in AWS (Amazon Warehouse Services), Microsoft Azure, Red Hat, etc., are in high demand. While some companies are directly building data pipelines on the cloud, others are migrating their existing systems to cloud servers. 2. Greater Budget Allocation for FinOps Another trend is the need for data cloud cost optimization. Top vendors like BigQuery and Snowflake are already talking about ways to optimize the data cloud cost and make cloud services more cost-effective to businesses from various industries and markets. Financial managers are becoming a part of data teams to ensure that their data engineering strategies and processes will deliver the necessary returns. While there aren’t enough best practices in the industry (data engineering is still in its early stages), data teams are finding ways to overcome the challenges and make their cloud-based data architecture more agile, flexible, scalable, and future-proof. The cost of ownership is also a crucial topic of discussion. 3. Usage-Based Data Workload Segmentation In the current scenario, companies are focusing on using a unified cloud-based data warehouse. For example, AWS data engineering is popular for offering data warehousing services to several business enterprises. However, the same type of database cannot be suitable for all kinds of data workloads. Experts predict that organizations will shift from data warehouses to data lakes where different databases and tools are individually organized and grouped into a unified setup. This can make the data architecture cost-effective and increase its performance. 4. Data Teams with Higher Specializations Though data engineers are in short supply due to the complexity of the job, data teams will continue to expand and include professionals with more specializations. For example, the data teams will have data engineers, data analysts, data scientists, analytical engineers, etc., to handle different aspects of establishing and using the data architecture in an enterprise. DevOps managers, finance managers, data reliability engineers, data architects, data product managers, etc., are other specializations we will see in future data teams. 5. Metrics Layers in Data Architecture In traditional data pipelines, the metrics layer (also called the semantics layer) is in the middle, between the ETL (extract, transform, load) layer and the cloud data warehouse. It defines the metrics for the values in the data tables and ensures consistency to eliminate errors during business analytics. Experts predict that the metrics layer will have an addition of a machine learning stack that has its own infrastructure. The ETL layer will continue to do its job, but the data will flow through the machine learning stack, which will help data scientists choose the right metrics for the given data. One day, the metrics layer and the ML stack will be combined to work as a single automated unit. 6. Data Mesh The concept of data mesh is one of the emerging DE trends discussed by many top companies. This new architectural model is said to help organizations overcome the limitations of traditional data warehouses and centralized data lakes. Date mesh is the decentralization of data governance and ownership. As discussed in the previous trends, domain-specific data platforms, tools, and databases will be established for greater efficiency. The idea is to build resilient, dynamic, and agile data pipelines that offer more autonomy, interoperability, and control to every member of the data team. However, establishing a data mesh requires more skills and tools. However, centralized data warehouses will continue to exist until enterprises can successfully build and deploy data mesh architecture. 7. Increase in Success of Machine Learning Models In 2020, a report by Gartner shows that ML models had only a 53% success rate. That too when they were built by companies with strong AI foundations and prior experience. It means even three years ago, only half the machine learning models could be deployed accurately and effectively. However, the success rate has been increasing over time. Soon, a greater percentage of the ML models can be successfully deployed by organizations. Of course, this will be possible when businesses overcome challenges such as misalignment of needs and objectives, overgeneralization, testing, validating issues, etc. 8. Changes in Cloud-Premises Architecture The architecture for data flow within an enterprise usually combines three different software applications. Databases from different departments (CRM, CDP, etc.) are connected to the data warehouse. The business intelligence and data visualization tools are connected to the other end of the data warehouse. Data flow occurs only in one direction. However, in modern data engineering, the data flow will occur both ways. The next-gen cloud data architecture will be bi-directional and allow data

Yashica Chopra
August 25, 2023
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7 Top Digital Transformation Companies in the United Kingdom

Digital transformation is a continuous process of adopting new technologies and data-driven models to gain a competitive edge and increase business ROI. Here, we’ll discuss its importance and the top digital transformation companies in the UK. Technology is essential for a business to survive in today’s world. From a startup to a multinational enterprise, every business organization needs to invest in relevant technologies to manage resources, speed up daily processes, enhance customer experience, and increase revenue. This indicates a strong need for digital transformation. B2B and B2C organizations should revamp their outdated systems and digitalize their processes. However, this is a continuous process and involves various elements. From experts to analysts to top management, mid-level decision-makers, employees, and stakeholders, many people are a part of digital transformation. Digital transformation companies have a prominent position because of their extensive range of services. In this blog, let’s find out more about digital transformation, its importance, and the top service providers in the UK. What is Digital Transformation? Digital transformation is using digital technologies to revamp existing systems or create new systems, business processes, work culture, and customer experiences in an enterprise. Data is stored digitally in a centralized database (data warehouse or data lake) and is connected to different applications to allow data analytics in real-time. Digital transformation brings agility, scalability, and flexibility to a business. It provides a competitive edge and allows businesses to make proactive decisions. What is Digital Transformation Consulting? Statistics show that 89% of large and global enterprises have invested in digital transformation and artificial intelligence. However, only 31% of these companies have achieved the expected results and revenue. It’s a clear indication that spending money on digital transformation without a comprehensive strategy and clear guidance will not be beneficial to the business. That’s where consulting companies play a vital role. Digital transformation consulting is the process of hiring an offshore service provider or a third-party consultant to provide end-to-end services to digitally transform the business process and achieve the expected results. Digital transformation experts from consulting companies understand your business vision, mission, internal systems, end goals, etc., to create a foolproof plan for digitalizing your business at all levels. The consulting company will also upgrade the existing systems, build new ones, and strengthen your IT infrastructure. The consultants will work with your employees to streamline data flow between different applications. Furthermore, they offer long-term maintenance and support services to ensure the systems are working without glitches. Top Digital Solution Providers in the UK 1. DataToBiz DataToBiz is one of the best digital strategy agencies in the UK, with clients from different continents around the globe. The company offers end-to-end solutions to help SMBs, MSMEs, and large enterprises adopt the latest technology like artificial intelligence, machine learning, data science, business intelligence, etc. It provides comprehensive data engineering and management solutions to streamline data flow and use real-time data for advanced analytics. PrepAI, HirelakeAI, Virtual Try-On Platform, etc., are some products developed by the company. A few services offered by the company are as follows: The company promotes digital transformation to speed up decision-making and provide a competitive edge to businesses from different industries. Whether manufacturing, healthcare, supply chain, EdTech, FinTech, surveillance, or travel, the company knows how to help clients succeed. From maximizing efficiency to boosting revenue, DataToBiz assists enterprises in effectively overcoming business challenges and achieving their goals. It has a transparent and flexible pricing system and is a certified cloud partner with AWS, Microsoft Azure, and Google. 2. Cognizant Cognizant is a global digital transformation company with clients from different industries and sectors. It helps enterprises transform their business experiences by reimagining the processes and modernizing technology. The company provides services to unlock business potential and stay up-to-date in today’s fast-changing world. It develops responsive technologies without ignoring social and environmental responsibility. It ranked 194 among the Fortune 500 companies in 2022. The services offered by the company are listed below: Cognizant also offers research services in areas like Metaverse, future-ready cities, deep green, future-ready business benchmarking, and more. It integrates data and analytical tools with various enterprise systems to provide real-time insights for effective decision-making. The company believes in engineering excellence through high-end technological solutions. Furthermore, the company’s digital strategy speeds up digital adoption and streamlines change management in clients’ businesses. 3. HCL HCL Technologies was founded in 1976 and is one of the leading IT companies in the world. It has over 2000 patents and 10,000 clients, with a presence in many countries. The company’s products and services are used by large enterprises to revamp their internal processes and stay ahead in competitive markets. The company works with establishments from various industries and promises world-class innovation. It has many top service providers in its ecosystem (AWS, RedHat, Dell, Google, Intel, Microsoft, etc.). The company has categorized its services into four areas of expertise, such as: The company is also focused on sustainability and aims to provide long-lasting results to its clients and stakeholders. HCL Technologies has divided its ecosystem to cater separately to start-ups and large enterprises. With a tagline of Supercharging Process, the company promises to offer industry-leading capabilities to help clients transform their businesses across all verticals. 4. Boston Consulting Group Boston Consulting Group (BCG) is a global consulting firm with 100+ offices in 50+ countries worldwide. It works with many Fortune 500 companies and has an annual revenue of $11.7 billion. The company provides various services to help businesses unlock the power of technology and expand their reach in global markets. It has expertise in many fields, ranging from finance to marketing, manufacturing, strategy management, people management, etc. The company has a unique collaborative model that enables it to revamp the processes at all levels and departments in the client’s enterprise. It offers the following services: BCG also offers services to tackle climate change and promote sustainability in an enterprise. It helps organizations build technologies and IT systems for the future. The company offers scalable services for artificial intelligence adoption in several industries, such as aerospace, education,

Yashica Chopra
August 24, 2023
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Top 10 Benefits of Procurement Analytics – Why Is it Important?

Procurement analytics is much more than just spend analysis. It can help all departments in the business to correct and strengthen their strategies and increase overall efficiency. Here, we’ll discuss the benefits of procurement analytics for an enterprise. Procurement is crucial for a business. It influences the various elements of the supply chain, right from production to quality control to distribution of the goods. With such an important role, it’s no surprise that businesses need to adopt the latest technologies to stay up to date in the dynamic global market and survive the competition. In many enterprises, the procurement teams are already handling cross-functional activities and working with teams from other departments. In fact, according to a survey by Procurious, more than 81% of procurement teams feel pressured to be more effective when responding to supply chain challenges. While this is alarming, the good news is that close to 80% of CFOs intend to maintain or increase enterprise digital investment. Procurement analytics is the process of using data and technology to help procurement teams make better, faster, and more efficient decisions. Instead of relying on guesswork or outdated reports, the teams can use real-time analytics to choose the raw materials, vendors, procurement methods, transportation routes, and so on. As per the report by Verified Market Research, the global procurement software market will touch $9.5 billion by 2028 with a CAGR (compound annual growth rate) of 7.6%. In this blog, we’ll read more about the benefits of procurement data analysis and how businesses can overcome challenges to fill the gaps in skills and technology. Why is Data Analysis Important in Procurement? Procurement analytics involves data collection from multiple sources (and ERP systems) and the analysis of this data to derive actionable insights for faster decision-making. The collected data is categorized into different segments based on the business KPIs. The analytical reports are shared using business intelligence or data visualization tools. However, procurement and spend analysis are much more than data visualization reports. It helps business enterprises make use of historical and current data to determine the best way forward in managing vendors, suppliers, and other members of the supply chain. The ultimate aim of procurement analytics is to optimize resources and increase ROI while enhancing customer satisfaction. Types of Procurement Analytics How can Procurement Analytics Benefit Your Business? CPOs (Chief Procurement Officers) have a great responsibility on their shoulders. They need to ensure the cost of procurement is within the budget without compromising quality and also maintain good partnerships with vendors. At the same time, CPOs have to consider various business goals and align the department goals accordingly. Fortunately, procurement analytics can provide a comprehensive solution to all these aspects and more. Let’s look at the various benefits of using purchasing analytics in the business. 1. Resource Allocation How to manage resources for the entire business? Are there areas in a business that is overspending? Can the organization reduce expenses without cutting corners? The answers to these questions can be found by relying on procurement analytics. That’s because the various activities of procurement analytics are interdependent and influence one another. For example, by monitoring inventory, the teams can determine the usage of different materials within the businesses. It helps track which items are necessary and which can be procured in fewer quantities to prevent overspending. By optimizing resource allocation, the business can improve the spending management indicators and increase opportunities to save costs. 2. Risk Management Countless things could go wrong during the procurement process. External factors can lead to delays, damages, and other issues, resulting in losses for the business. Even if an enterprise has been following the same procurement process for years, the element of risk will always remain. However, procurement analysis can help in managing this risk efficiently. It empowers the teams to identify bottlenecks and challenges that can and cannot be controlled by the business. Then, these issues are addressed individually to establish a risk management policy and minimize losses. For example, an organization with vendors from other countries has to create a risk policy to handle geographical border restrictions, weather-related delays, socio-political factors like wars, etc., to ensure that the supply keeps coming despite the adversities. 3. Data-Driven Decisions Data is the key to making informed decisions in today’s world. Data analytics help combine past and present data to derive meaningful insights for identifying trends, understanding the challenges, and becoming proactive to make the most of market opportunities. Procurement analytics will help the enterprise track the demand and supply in the market and adjust the orders accordingly. Demand forecasting reports help stay one step ahead of competitors and meet customer demands before other businesses can take advantage. 4. Supply Chain Transparency The supply chain network of a business can be lengthy and complex. Maintaining transparency throughout the process can be difficult without using the right technology. That’s where using analytics in procurement helps organizations. Data is collected from different sources and made available to teams from various departments across the business. This allows the finance, IT, marketing, and customer service teams to use the data to improve sales and customer experience. For example, customers around the world are becoming more aware of sustainability and eco-friendly practices. Many customers want to know where and how a business procures its materials. A transparent supply chain makes it easy to share this information with customers. In fact, some brands use it as a marketing strategy to attract customers. 5. Category Management Category management is a part of spend analysis and vice versa. The spend categories are created by grouping similar types of purchases under individual heads. Spend analysis gives the procurement teams the necessary data to segment the purchases and expenses by creating a basis for category structure. It is the starting point of category management and allows businesses to have a clear picture of how much they spend on each category and ways to optimize the expenses. Not only do procurement and spend analysis help with category management but also provide businesses with the necessary insights to link the strategies

Yashica Chopra
August 22, 2023
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7 Top Artificial Intelligence Companies in UAE

Artificial intelligence has gained prominence in Middle East countries. Many businesses in UAE are revamping their existing processes to achieve greater success through AI. Here, we’ll discuss the top AI companies in the UAE and the benefits of partnering with them. UAE has been a hub for the oil and gas industry for decades. However, the region is aiming to become a leading center for ICT (information and communication technology) industry for international trade. Middle East countries are setting up free trade zones to promote the use of software products and services in all industries. Artificial intelligence, cloud computing, cybersecurity, the Internet of Things (IoT), etc., are gaining popularity in the UAE market. In this blog, we’ll read more about AI and the list of artificial intelligence companies in the UAE that offer tailor-made services to various enterprises. What is Artificial Intelligence? Artificial intelligence is an umbrella term encompassing various techniques, technologies, processes, applications, and models. It includes fields like machine learning, deep learning, computer vision, etc., which are used for an array of purposes by different businesses. Every industry needs AI in today’s world to adopt the latest technologies and survive market competition. The global AI market is expected to reach $407 billion by 2027, according to a report by MarketsandMarkets. As per Forbes, 60% of businesses say AI will enhance customer relationships and productivity. Most SMBs and large enterprises partner with AI consulting firms to digitally transform their business processes and adopt AI to achieve the desired results. This helps them save time, money, and resources while reducing the risk of losses. AI experts from offshore consulting companies create the necessary strategies to implement, integrate, and maintain AI applications in an organization. Is Artificial Intelligence in Demand in UAE? Yes. The UAE government has ambitious plans to promote the adoption of artificial intelligence in the country. It has adopted the National Artificial Intelligence Strategy 2031 and established Many companies that are entering the market regularly to accelerate the use of AI in the region. Apart from these, local businesses and enterprises work with several offshore AI firms to increase their productivity, ROI, and revenue. Top Artificial Intelligence Companies in UAE 1. DataToBiz It offers AI platform customization, pilot implementation, and full-scale digital transformation to adopt the data-driven model in a business. The company takes care of all the steps from start to finish and provides complete assistance and expert support at every stage. From strengthening the supply chain to enhancing customer experience, increasing productivity, quality, and business efficiency. DataToBiz offers various services, such as: The company has clients from the Middle East, North America, South America, Asia, Australia, and Africa. It is a certified partner of Microsoft, Google, and AWS (Amazon Warehouse Services) with over 97% client satisfaction rate. Businesses can use the real-time actionable insights provided by DataToBiz to make effective decisions, create innovative products, and amplify revenue. 2. Accubits Technologies Accubits is an AI company with clients from the Fortune 500 list from around the world. It works with tech startups to provide comprehensive software product development services and technological solutions. The company is known for building enterprise-grade blockchain platforms with greater transparency, security, and efficiency. It combines the world of blockchain and web3 using advanced technologies. The company’s AI services include generative AI development and integration, automation, computer vision, and consultancy services to help various organizations benefit from using artificial intelligence for day-to-day work. Accubits also provides business intelligence solutions to drive accurate insights for decision-making. The company offers the following services: Accubits has been named the most promising brand in 2021 by the Economic Times. It promises ROI plus (Return of Innovation Positive), a new metric developed by the company to determine how their knowledge is helping clients achieve success. The company has an active presence in UAE and the Middle East. 3. Silwana Infotech Silwana Infotech is a software development and AI company in UAE offering transformative and technology-driven solutions to clients from several industries. It has more than two decades of experience in the IT industry and follows a client-first approach to provide scalable, flexible, and result-oriented solutions to each business. The company primarily works with enterprises from the MENA region (Middle East and African Countries). It uses cutting-edge technologies to cater to client’s requirements and help them achieve the desired results. The company has offices in nine locations and has worked on 700+ projects in more than ten industries. Silwana Infotech offers the below services: The company starts by analyzing the feasibility of the project before developing and implementing the right technology and tools in a business. It also offers support and maintenance services to ensure the business doesn’t suffer from disruptions due to technical glitches. It offers onshore and offshore services, along with a hybrid model that combines both business models. 4. Citrus Consulting Services Citrus Consulting is a technology firm that offers several IT-based services to clients in the UAE. It provides AWS hyperscaling services to help businesses expand and develop their IT infrastructure on the cloud. It believes in innovation to make systems and processes more agile in an enterprise. The company uses modular solutions to provide clients with a choice to select their technology stack instead of relying on a single tool. The company is a hybrid cloud expert and also specializes in information and cybersecurity system implementation and development. It works with businesses from the Middle East and African regions and India in assisting enterprises through their digital transformation journey. Citrus Consulting Company provides the following services: The company has a robust ecosystem and belongs to the Redington Group, known for its presence in the IT and mobile industry for many decades. It promotes the use of new-age technologies like AI, IoT, robotics, big data analytics, and 5G to help businesses overcome challenges, automate processes, and optimize workflow to increase ROI. 5. EORA.ai EORA is a group of companies that uses machine learning, natural language processing, computer vision, and data science to provide unique solutions to businesses. With offices in Moscow and Innopolis,

Yashica Chopra
August 19, 2023
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15 Common AI Mistakes to Avoid: Ensure a Smooth AI Journey

Artificial intelligence offers endless benefits to a business but can be overwhelming to implement without proper guidance and support. Here, we’ll discuss the common errors enterprises make in AI implementation along with the ways to avoid them. Artificial intelligence has been a part of the global market for years. While it has several definitions, AI is mainly the science and engineering of making machines intelligent. It combines computer science and datasets to enable quicker problem-solving. Many SMBs, MSMEs, and large enterprises are adopting AI technology and tools for various purposes. A research report shows 44% of companies in the private sector will adopt AI in 2023. According to Statista, AI is mainly used for managing data as a business asset, establishing data culture, driving innovation, performing data analytics, and building a data-driven enterprise. However, several business organizations have suffered from artificial intelligence failures. In fact, various studies show that 70% of companies have minimal or no impact of AI, and a whopping 87% of data science projects don’t make it to production. In a way, AI mishaps are one of the reasons for organizations to be wary of adopting advanced technology for digital transformation. For example, the automated hiring algorithm used by Amazon turned out to be biased against women and hired only white men (due to biased training data). A real estate tycoon in Hong Kong filed a lawsuit against a business that sold him an AI robot to manage his funds. The robot lost around $20 million every day instead of increasing the funds by making the right investment decisions. It’s crucial to understand where things go wrong and avoid such mistakes to successfully implement AI technology in a business. In this blog, we’ll read about the common AI mistakes every business should avoid and ways to achieve the desired results. What are the Most Common AI Mistakes to Avoid? 1. Half-Hearted Attempts Artificial intelligence can offer a multitude of benefits to a business. However, it requires heavy investment in building a strong IT infrastructure and training employees to work with the latest tools. Making half-hearted attempts or investing in AI for the sake of it is a sure way to generate losses. AI adoption requires planning, implementation, and continuous tracking to deliver results. Haphazard processes will only waste business resources and lead to additional complications. To prevent such issues, businesses should take the time to develop a strategy for AI adoption and follow it. 2. Lack of Data Quality Is your data large enough to make AI effective? This is one question many people ask since AI is associated with large datasets. However, businesses forget to consider data quality and its impact on artificial intelligence. The AI model is as good as the data used to train it. If businesses don’t provide high-quality data input, the model will not deliver accurate results. Lack of data quality is another major reason for AI failure in enterprises. This can be avoided by investing in proper data systems and ETL (extract, transform, load) models to collect, clean, format, and process the data before it is fed into AI models for training. Data management is necessary to avoid skewed or incorrect models. 3. Unclear Business Goals Why should a business invest in AI? What problems does the top management wish to solve using artificial intelligence? Which business goals can be achieved through AI adoption? Every enterprise should have clear answers to such questions before investing in AI. Simply copying a competitor is likely to result in failure. Establish definite and measurable business goals. Align these goals with the business vision and mission. Then create an AI adoption strategy that supports the business goals and objectives. Evaluate the impact the AI model would have on the establishment and calculate the expected ROI. The trick to avoiding AI failure is to spend more time strengthening the foundation instead of building AI on weak bases. 4. Not Focusing on Change Management AI adoption requires many changes across the organization. The internal processes, IT systems, employee working methodologies, and organizational culture have to be changed and revamped to align with how AI systems work. Quite a few businesses don’t pay enough attention to these changes. They don’t have a comprehensive plan to implement the changes cohesively at each level. This results in disruptions, miscommunication, delays, and unexpected losses. Companies offering AI consulting services insist on developing a change management strategy to ensure employees, management, systems, and processes are in sync and work towards the same goals. It’s vital to address the cultural and behavioral aspects of AI adoption to overcome roadblocks and ensure a smoother transition from outdated methods to the latest ones. 5. Relying on Black Box Models AI models are complex and hard to understand. There’s no denying this statement. However, when a business relies on such black box models (ones that offer almost no explanation of how the algorithms work), it creates opacity in the enterprise. Lack of transparency and accountability can lead to many issues for the business. Who will be responsible for the wrong insights? Avoid using black-box AI models in the organization. Work towards building transparent models and maintaining clear documentation to understand how things are done. Businesses that cannot afford to build AI models from scratch can partner with AI companies to customize existing tools and increase transparency. Put in extra effort to explain the process to employees and establish procedures that make people accountable. 6. Not Enough Expertise Introducing artificial intelligence in a business is no small task. AI models are best handled by experts with the necessary domain knowledge. Asking the existing talent pool to use AI technology without proper training is likely to cause errors and additional problems. When planning the digital transformation of a business, it’s important to identify the talent gap and find ways to fill it. Organizations can hire an in-house team of AI experts to initiate the process or rely on offshore service providers. Building a team from scratch is cost-intensive and time-consuming. However, working with AI companies is quicker, cheaper, and more effective.

Yashica Chopra
August 17, 2023
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10 Steps to Create a Data-Driven Culture

With proper planning and implementation, enterprises can effectively use data to make business decisions. However, a strong data culture is still a theory for many business organizations. Here, we’ll discuss the steps to create a data-driven culture in an enterprise. Businesses need to work with quality data to make effective business decisions. While we cannot ignore the importance of human expertise, combining both is the best way to boost a business in a competitive market. This requires using data and data analytics to make decisions. Statista reports that the global big data analytics market will reach $655 billion by 2029, while the predictive analytics market is estimated to touch $41.52 billion by 2028. A business organization can enjoy the benefits of data analytics and business intelligence by adopting a data-driven culture. Another report shows that 57% of leading brands are already using data to drive innovation. So how do you create an effective data-driven culture in your enterprise? Let’s find out in this blog. But first, let’s dive into the basics. What is a Data-Driven Culture? Is data the key to a data-driven culture? Absolutely! A data-driven culture is where the workforce uses statistics, analytics, facts, insights, predictions, etc., to make everyday business decisions and optimize their tasks. Team leaders, managers, and C-level executives use insights to understand various elements of work and how these affect business performance. Many components contribute to creating a data-driven culture in an organization. However, the major aspects are as follows: 1. Data Maturity Data maturity refers to the process of storing and retrieving data over time. It depends on your data governance policies and how well you manage and maintain the datasets with accurate tags, metadata, etc. 2. Data Leadership Data leadership defines the role of leaders and decision-makers in managing business data. These people understand the importance of quality data and help maintain a work culture where decisions are made based on data analytical reports. 3. Data Literacy Data literacy is the act of ensuring business data is structured, accessible, reliable, and accurate. It also involves training employees to understand and use datasets effectively for day-to-day work. Investing in a data-driven culture requires expert guidance and support. SMBs and large organizations partner with a reputed data analytics company to revamp their internal processes and work culture the right way. What are the Steps in Data Management? The data management framework has to be structured and aligned with the business process. Here’s how to implement successful data management in your enterprise and create a strong foundation for data-driven culture. Steps to Create a Data-Driven Culture Understand that creating a data-driven culture is not limited to technological investments. The focus is equally on changing the existing work culture to help employees use new technology and tools at work. The following steps will help you build an effective data-driven culture in your enterprise. 1. Start with the Top Management The top management and C-level executives play a vital role in influencing other employees. They need to understand the importance of data-driven solutions and establish it in the organization. When the management makes it a norm to use data and evidence for decision-making, employees will follow it over time. For example, the team leader or manager can allocate a few minutes at the beginning of a meeting to go through the analytical reports and observe whether the proposals are backed by data. Then, they can discuss the proposals and the reports to help other employees realize why they should work with data. When the top management sets an example, it becomes easier for employees to adapt to the changes. 2. Choose Metrics Carefully How do you analyze the business performance? It can get complicated and confusing without metrics. Every enterprise has its own metrics for analytics. However, there’s no guarantee that the existing metrics are correct or suitable for accurately measuring the business. For example, many businesses use competitor analysis because they need to keep track of what other brands in their industry are up to. An FMCG company will have to decide its pricing and marketing strategy based on customer behavior, market trends, and competitor’s offerings. Not factoring in either factor can result in skewed analytics, which invariably leads to wrong decisions. Define metrics carefully and make sure they are always aligned with the business vision, goals, and industry standards. 3. Don’t Isolate Data Scientists One major mistake many organizations make is to keep the data scientists and business leaders in separate units. While the analytical reports are shared between the teams, the people responsible are not always collaborating and usually work in isolated teams. This can affect the quality of analytics and will soon widen the gap between reality and analysis. Leading brands have managed to avoid this issue by eliminating the boundaries between data scientists and business leaders. The staff (team members) is rotated between different departments to keep communication flowing. Another method is to ensure that the top management has the necessary technical know-how to directly interact with data scientists and work with them. While it is not necessary to replace existing executives with AI and ML engineers, it is important to train them in the basics. 4. Provide Access to Data A common complaint from employees is that there don’t have access to data or analytics at work. It takes too much time and energy to obtain even the basic data, and this isn’t enough to make data-driven decisions. Despite democratizing the storage systems, analysts aren’t given access to information from other departments due to different constraints. This challenge can be handled by identifying the data related to the KPIs for the project/ quarter and providing enterprise-wide access to this information. For example, if the sales analyst has to create a demand forecasting report, they should have access to information about past sales, customer feedback, inventory, etc. While data security is a concern, it can be handled through effective data governance and by setting up authorized access employees based on their project requirements. 5. Assess Uncertain Aspects To build an