Page 15 – DataToBiz

Pawan Chabra
January 23, 2024
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Top 7 Data Warehousing Consultants for US Travel & Tourism 2024

In 2024, data-driven decision-making is driving the travel and tourism industry. Data warehousing consulting companies offer personalized experiences and streamline operations. Here are the leading data warehousing consulting companies for US travel and tourism. The travel and tourism industry stands at the crossroads of innovation with data-driven decision-making being the critical driver. As destinations strive to offer personalized experiences and streamline operations, the role of data warehousing for tourism has emerged as a linchpin for success. With close to 70% of all travel bookings being made online, it is the right time for the industry to move towards building a positive experience for the long term. The industry relies on several data sources, from customer preferences and booking patterns to operational logistics and market trends. A comprehensive data warehousing strategy becomes the backbone, seamlessly integrating, managing, and analyzing this wealth of information. This not only enhances operational efficiency but also empowers businesses to anticipate and meet the dynamic demands of today’s travelers. Yet, the implementation of effective data warehousing solutions isn’t a standalone endeavor; it necessitates a strategic partnership with data warehousing consulting companies. Beyond the intricacies of technology, consulting services bring invaluable expertise to the table, ensuring that data warehousing aligns seamlessly with organizational goals. 7 Top Data Warehousing Consulting Companies for US Travel & Tourism in 2024 Selecting the right data warehousing consulting partner sets the right foundation for a travel and tourism business. Here are the 7 top data warehousing consulting companies for US travel & tourism in 2024: DataToBiz DataToBiz has established itself as a go-to partner for organizations seeking comprehensive and cutting-edge travel analytics and managed analytics solutions. With a robust suite of services, the company excels in providing expert guidance through its data warehouse consulting, helping clients navigate the complexities of design and infrastructure analysis. Managed analytics professionals at DataToBiz not only recommend optimal alternatives, such as cloud or hybrid data warehouses but also craft robust data integration strategies for managed analytics for the travel industry. Going beyond consultation, the company demonstrates prowess in the development and implementation of data warehouse solutions, tailoring them to meet specific organizational needs within defined timeframes and budgets enabling data-driven decision-making in the tourism and travel sector. Specializing in seamless data migration strategies, DataToBiz envisions a future where data resides in the cloud, offering dedicated support services to ensure ongoing functionality and performance monitoring. With a commitment to holistic data solutions, DataToBiz emerges as a trusted partner, transforming data into a strategic asset for sustainable business growth. Capgemini Capgemini stands as a renowned leader in data management, specializing in providing tailored data warehousing services for the travel and tourism industry. Recognized for their expertise, Capgemini excels in seamlessly integrating disparate data sources, constructing resilient data lakes, and crafting sophisticated data-driven strategies. With a commitment to excellence, they offer comprehensive solutions that empower businesses in the travel and tourism sector to harness the full potential of their data for informed decision-making and operational efficiency. Infosys Infosys, a prominent IT services provider, stands out as a premier data warehousing company with substantial expertise in the US travel and tourism sector. Renowned for its capabilities, Infosys excels in implementing cutting-edge data platforms, automating processes, and upholding robust data governance standards. With a proven track record, Infosys empowers organizations in the travel and tourism industry to leverage advanced data warehousing solutions, fostering efficiency, reliability, and strategic decision-making. Cognizant Ranked among the top data warehousing consulting companies for US Travel & Tourism in 2024, Cognizant brings a robust emphasis on data analytics and digital transformation to the table. Leveraging their expertise, they assist travel and tourism companies in constructing modern data warehouses, extracting actionable insights crucial for informed decision-making. Cognizant’s proficiency extends to providing cloud-based solutions, capitalizing on their industry-specific knowledge to deliver valuable assets for businesses navigating the dynamic landscape of travel and tourism data management. With a focus on innovation, Cognizant stands as a strategic partner for organizations seeking cutting-edge solutions in data warehousing. Mu Sigma Mu Sigma, a global leader in data science and analytics, emerges as a key player in delivering innovative data warehousing solutions tailored to the unique needs of the travel and tourism industry. Renowned for its expertise in predictive analytics and machine learning, Mu Sigma empowers businesses to optimize pricing strategies, personalize offers, and enhance customer engagement. As the world’s largest pure-play Big Data analytics and decision science company, Mu Sigma collaborates with over 140 Fortune 500 companies, amplifying productivity and providing meaningful solutions by integrating people, processes, and platforms. ThoughtSpot ThoughtSpot emerges as a rising star in the data analytics arena, providing a distinctive search and navigation platform designed to simplify data exploration and analysis for business users, eliminating the need for technical expertise. In the context of the travel and tourism industry, ThoughtSpot’s innovative solution proves especially valuable. It facilitates the democratization of data access, empowering teams within travel and tourism companies to make informed, data-driven decisions. ThoughtSpot’s commitment to travel revenue management analytics aligns with the growing demand for intuitive tools, making it a compelling choice for organizations seeking to enhance their analytical capabilities in the dynamic landscape of the travel and tourism sector. IBM As a technological behemoth with a storied legacy in data management, IBM stands out as a powerhouse providing robust data warehousing solutions, including Db2 and Cloud Pak for Data. IBM’s unparalleled expertise in AI and analytics proves instrumental in enabling companies to achieve a profound understanding of their customers. By leveraging IBM’s cutting-edge solutions, businesses in the travel and tourism sector can unlock the potential for personalized experiences, enhancing customer engagement and satisfaction. IBM’s commitment to innovation continues to make it a strategic partner for organizations seeking to harness the power of advanced data warehousing in their operations. Industry Trends: Data Warehousing for Travel and Tourism Industry The travel and tourism industry is undergoing a data revolution, fueled by the explosion of digital bookings, mobile apps, and social media interactions. This has generated a treasure trove of

Kavika Roy
January 22, 2024
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eCommerce Analytics Simplified- Data Warehousing Challenges Solved by Managed Analytics

Data teams face different challenges while storing and analyzing intricate datasets in data warehouses. Find out how you can overcome these challenges by using eCommerce analytics offered by digital commerce managed services tools. Data and analytics play an important role in running an eCommerce business successfully. The analytics tools enable businesses to track and analyze business performance through reports and dashboards, giving meaningful insights. However, when dealing with extensive datasets, businesses face challenges related to storage and analysis. Data warehouses store and manage data to ensure that analytics tools can easily process it to extract meaningful conclusions by analyzing query results. In this blog, we’ll talk about the common challenges in data warehousing and how you can overcome them using managed analytics. What is data warehousing in eCommerce? In the context of eCommerce, data warehousing refers to collecting, storing, and organizing data sets from multiple datasets, enabling businesses to get insights and facilitate data-driven decision-making in eCommerce. Let’s have a quick look at the benefits of data warehousing in eCommerce. What are the common challenges of data warehousing? Data Quality: Errors and improper updates lead to inaccurate data which impacts data quality. As businesses are increasingly implementing digital commerce solutions, they may face the problem of unintentional data silos. This makes data integration difficult throughout the system. Data Accuracy: Inconsistencies may lead to inaccurate data in data warehouses. This further compromises the reliability of insights and reports generated from inappropriate data. Performance: Slow performance of data warehouses results in sluggish query speeds which makes it difficult for the users to make quick decisions. Advanced solutions for data warehousing in eCommerce optimize processes and enhance performance. eCommerce Data Analytics- simplified! eCommerce data analytics includes analyzing large data sets to understand market trends, and customer preferences, and obtain meaningful insights to find out what’s working and what’s not in your eCommerce business. Understanding eCommerce sales analysis allows business owners to make strategic decisions, bringing high productivity and profitability. It helps them to understand the patterns in customer behavior analytics in eCommerce, and their preferences to personalize marketing strategies that resonate with target demographics. Further, it makes it easy to adjust pricing depending on factors such as competition and demand. By using data analytics, businesses can send customized product recommendations to shoppers to increase customer engagement and sales. Also, it predicts future trends to tailor the marketing strategies to yield high ROI. What are the potential challenges in using data analytics on eCommerce platforms? Now let’s discuss the biggest challenges that eCommerce marketers face when dealing with data. Excessive Dependence on Vanity Metrics: Metrics such as page views or social media followers often look fascinating, however, do not correlate with customer engagement or conversions. Businesses should focus on high-priority metrics (cart abandonment, customer lifetime value, and conversion rates) to analyze the growth of their eCommerce business. Ignoring Updates to Data Sources: eCommerce solution providers must update their data sources in real-time to ensure the accuracy and integrity of data. Data Silos: Data silos result in a fragmented view of business performance. Therefore, it is essential to integrate data sets to give a comprehensive view of the business, facilitating prompt decision-making considering all aspects of business. Wrong Interpretation of Data: It is easy to misinterpret data when the context is lacking. For example, a quick increase in website visitors may initially appear positive, but it could be due to a controversial ad or the virality of bad reviews floating around the Internet. Thus, the analytics team must understand and cross-reference data to ensure accuracy. Managed Analytics Tools Now let’s find out some of the top tools managed analytics tech stack include: Data Storage: Amazon Athena, Azure Synapse Analytics, Amazon Redshift, Azure Data Lake Storage, SAP, Amazon S3, MongoDB, MySQL, Azure Integration Services, Hadoop, Google Big Query, and Microsoft SQL Server Data Integration: Microsoft SQL Server, AWS Glue, Python, Apache Airflow, Talend, and Azure Data Factory Business Intelligence: Tableau, Microsoft SQL Server, Power BI, Metabase, MicroStrategy, Excel, Qlik Sense, and Redash Data Ingestion: Kafka, Amazon Kinesis, and Microsoft Azure Data Processing: Microsoft SQL Server, Apache Spark, and Databricks ERP Systems: Oracle Enterprise Resource Planning Cloud, Microsoft Dynamics 365, and SAP S/4 HANA Cloud Partners: Azure, AWS, and Google Cloud Platform How can Managed Analytics Services Simplify Analytics of Enterprise eCommerce Solutions? Managed Analytics are indispensable for eCommerce analytics solution companies. They transform raw data into practical insights ready for implementation. With the assistance of analytics experts, you can obtain the most out of existing business data, and make precise decisions with the help of data-driven tactics. How do Managed Analytics work? The key steps of managed analytics include: Data Collection: Collects data from diverse sources such as databases, files, or APIs. Storage and Cleaning: Stores collected data in a centralized system such as a data warehouse to ensure accuracy and consistency. Analysis and Modelling: Uses advanced analytics tools and algorithms to examine patterns and trends and generate insights to make informed decisions. Visualization and Reporting: Presents insights in understandable formats including visuals, dashboards, and automated reports, making it easy to comprehend information and take necessary action. Continuous Improvement: Monitors the performance of the organization, optimizes processes, and enhances efficiency through regular improvements. How do Managed Analytics Services help Manage eCommerce Analytics? Data Governance: Data governance sets the guidelines and standards to handle eCommerce data to ensure its reliability, accuracy, security, and consistency. It safeguards eCommerce data such as customer information, transaction records, and confidential information to maintain privacy. Big Data Implementation: With Big Data, you can easily manage large amounts of data generated in eCommerce including customer interactions, transactions, and much more. It also tracks patterns and trends to offer predictive analysis. Data Architecture: A robust data architecture organizes and structures eCommerce data, optimizing data flow. It also makes it easy to integrate data from different sources and access it. Data Lake: Data lakes serve as central repositories to store structured and unstructured eCommerce data, making it easy to store, process, and analyze all

Yashica Chopra
January 20, 2024
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6 Top UK Real Estate Analytics Firms Advancing into the Data Age

The real estate sector in the United Kingdom is going through a transformational phase in recent times. Here, we’ll discuss the top real estate analytics consulting firms in UK and their role in promoting technological adoption in the industry. The real estate market constantly faces challenges, be it inflation or socioeconomic conditions. According to CBRE, the UK real estate market had been an uphill task as the interest rates hit a fifteen-year high. The asset values declined, making it hard for investors to buy a property and maintain it. With the inflation falling in at the end of 2023, real estate companies in the UK are hopeful. Moreover, with the elections scheduled, many investors and brokers feel things will get better in the second half of 2024. The report shows that commercial real estate will be more attractive this year since the yields are likely to stabilise. In such conditions, it’s even more crucial for real estate agencies to stay one step ahead of the market changes to provide investors with worthy properties. Competition is also high, with around 146,100 private real estate companies in the UK. These businesses had a yearly turnover of 72.81 GBP in 2023. If the conditions become favorable, the market share will increase by a greater margin. The agency can achieve its goals by investing in real estate business intelligence to derive actionable and real-time property analytics for effective decision-making. From identifying potential properties for sale to being the first broker to reach out to clients, real estate analytics services can help you streamline and accelerate your goals. Let’s find out more about consulting firms offering real estate analytics in the UK. What is a Real Estate Consulting Firm? A real estate consulting firm offers managed analytics for real estate agencies and brokers. The consulting firms have diverse responsibilities and help with digital transformation, data governance, data warehousing and engineering, business intelligence, etc., to unlock the power of real estate data. The service providers provide the necessary know-how, technology, tools, and expertise for strategic planning, implementation, and maintenance of data analytical tools. The primary purpose of a real estate analytics firm is to promote data-driven decision-making in real estate agencies, business owners, and investors. Conducting market surveys, identifying patterns and trends, managing portfolios, lease advisory, due diligence, etc., are some services offered by these firms. In short, partnering with a real estate analytics consulting company is the best way to digitise the business and gain a competitive edge. Top Real Estate Analytics Consulting Firms in UK DataToBiz DataToBiz is among the top real estate analytics consulting firms in the UK, offering end-to-end services to residential and commercial agencies, brokers, and corporate companies in the industry. It provides managed data warehousing for property development solutions to stay updated about the properties in the regions the business operates. The company uses business intelligence tools like Power BI to build customised dashboards for property management, investor analysis, market forecasting, etc. DataToBiz also builds tailor-made apps for property portfolio analytics. It enables real estate agencies to effectively use the right BI solutions for property investment and decision-making. The company is a certified partner of Microsoft, Google, and AWS. It follows a client-centric model to accelerate success and help clients achieve their goals. It has worked with over 300 firms from various markets and has more than 97% project satisfaction rate. DataToBiz combines technology, domain experience, and local expertise to empower real estate companies to build sustainable businesses and proactively handle market volatility. Deloitte Deloitte is a popular multinational company with a presence in many countries. Deloitte Real Estate combines property services with financial reporting and business advisory solutions to provide complete support to real estate agencies and corporate companies. It uses years of expertise to build and implement property financial reporting using BI tools and derive real-time construction project analytics. It helps address the various challenges faced when handling high-capital projects. The company also has a team to specifically handle real estate and tax concerns for private individuals/ residential clients. Deloitte gives importance to sustainability and climate concerns. It uses generative AI design to enhance urban development and planning without adversely affecting nature. As a real estate market intelligence service provider, the company understands the importance of data and its role in helping agencies, brokers, and investors make the right decision in a quick time. Deloitte has a solution called Real Estate Climate Value at Risk (RECVR) in partnership with Longevity to enable decision-making based on climate-risk information. This is a great tool for corporate businesses to choose commercial property. KPMG KPMG has completed over 150 years in the UK and is a well-known company offering auditing and tax services for businesses from various industries, including real estate. It provides customised services to effectively manage tax, assurance, and deal advisory, along with ESG (environment, sustainability, and governance) solutions. The company handles global asset management analytics for real estate agencies and corporate businesses with offices around the world. It supports businesses in adopting the latest technology to grab market opportunities and attract more clients. KPMG also provides consulting services for strategic formation and technology implementation in the industry. It assists businesses manage risks and challenges like taxation, regulation, sociopolitical influences, etc., to minimise losses. The company’s real estate BI solutions are aimed at providing the much-required foundation for agencies and businesses to navigate the changing market landscape and uncertainties. KPMG has been contributing to support Britain and its businesses to promote faster growth and development. Bain & Company Bain & Company is a global consultancy with a presence in 65 cities across 40 countries. The company offers tailored and integrated experiences to businesses to help them achieve better and quicker outcomes. It has a platinum rating from EcoVadis and is among the top 1% of companies that focus on high environmental, social, and ethical performance. The company has worked on over 580 service cases in the real estate industry by offering property data insights, building the necessary tools, and providing due diligence based on the client’s requirements. Bain & Company works with agencies, property owners, REITs, and others to assist them in handling various requirements and challenges. It provides several services,

Yashica Chopra
January 19, 2024
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10 Proven AI-ML Strategies for Early-Stage Tech Startups

Artificial intelligence is a powerful technology offering versatile solutions to businesses from different industries. Here, we’ll discuss the best AI-ML strategies for early-stage tech startups and the importance of hiring machine learning development services. Startups are popular these days, with more people willing to take the risk and become entrepreneurs. However, not many startups survive to see the light. After all, the markets are highly competitive, and a startup just doesn’t have the kind of support and brand image an established business has. Does it mean you should not take the risk? Of course not! It only means you should do better research and get the right guidance to overcome the challenges and strengthen your startup’s position in the market. Statistics show that 26% of people who start their own business say it is because they are ready to be their boss instead of working for another. In such instances, it is even more important to make the right decisions and investments when establishing a startup. So, what should be your primary focus in today’s world? The answer is artificial intelligence. With the global AI market estimated to reach $407 billion by 2027, you cannot afford to ignore the benefits of using artificial intelligence in your startup. Nevertheless, choosing a random AI tool will lead to adverse results. As an upcoming entrepreneur, you should leverage robust and comprehensive AI or ML strategies for your early-stage startup, especially if it belongs to the IT industry. You will need to work with a reliable Artificial Intelligence Development Company to understand the intricacies of using AI/ ML in your business. But… you have more questions, don’t you? Worry not. We will answer the major ones in this post. Shall we get started? What is AI/ML Strategy? An AI/ML strategy is a blueprint that guides you in choosing and implementing various AI applications in the business. It aligns the business strategy with the company’s mission, vision, and goals. The AI strategy has to be in sync with the overarching business strategy so that you have the right tools for the right job. Before you consider AI implementation for startups, you need to have a viable core business strategy. This allows the AI strategy to be the necessary fuel that powers your business. It also helps in bringing the various business processes together to create a cohesive and streamlined system that runs smoothly. Startup AI consulting companies focus on these aspects when offering strategies to implement AI and ML applications in your business. They use their expertise to understand your requirements and find the best solution. How AI is Used in Startups? Proven Tips for AI-ML Strategies for Early-Stage Tech Startups Innovative Product Design and Development AI-driven software development promotes innovation, creativity, and greater customer satisfaction. That’s because artificial intelligence is used to analyze customer preferences and market trends to derive insights, which help in designing the final product. AI also accelerates product development through automation and reduces the time-to-market. You can quickly launch your startup before competitors take advantage of the opportunities. Artificial Intelligence for Customer Service AI chatbots and virtual assistants with natural language processing (NLP) for startups can streamline customer service from the initial days to ensure the end users are happy with your business. AI can handle general queries, share user guides, generate tickets, and track the chat even when a human takes over. Additionally, a chatbot doesn’t get tired and can interact with several customers at once. Predictive Analytics for Decision-Making Predictive analytics is a part of advanced analytics that uses statistics and ML algorithms to determine the likelihood of a future outcome. Custom machine learning application development services allow you to use predictive analytics for various purposes, such as sales forecasting, machinery maintenance, predicting customer behavior, identifying new markets, etc. It helps make data-based decisions to effectively manage your startup. Streamline Sales and Marketing Startups need to constantly work on their marketing campaigns to gain visibility and attract target audiences. Cloud-based AI/ML solutions for startups help identify prospective customers and make it easy to create category-specific ads and promotions. You can create highly personalized campaigns for each section of your audience to increase sales. AI tools also help with sales forecasting. Machine Learning for Fraud Detection Online and offline frauds are a big concern for every business. As a startup, you cannot afford to have fake and fraudulent transactions in high volume. Luckily, artificial intelligence and deep learning for startups can analyze your business/ transactional data to detect signs of credit card fraud, money laundering, identity theft, etc. You can protect your startup from severe financial losses caused by such activities and avoid legal complications. Operations Management and Automation AI-driven product enhancement is highly effective in streamlining operations, reducing costs, shortening production cycles, improving quality, optimizing the supply chain, and managing inventory. By automating repetitive tasks, your employees can focus their energies on the core business processes and come up with innovative ideas to expand the offerings. Artificial intelligence can be implemented at all stages and levels of a business. AI-Powered Cybersecurity You cannot compromise on cybersecurity in today’s scenario. Hackers will target any business or individual. Statistics estimate that the global cost of online crimes will reach $23.84 trillion by 2027. According to the ISACA’s 2023 State of Cybersecurity report, 48% of businesses reported an increase in cyber threats in a year. AI-powered digital transformation for startups includes robust data governance and compliance protocols. You will get detailed documentation about how to set up a multi-layered security system to protect your startup from cybercriminals. Moreover, AI-based antivirus software is effective in detecting cyberattacks. Smart Resource Allocation Can we compare the resources of a startup to an established brand? No, right? Startups usually have to work with limited resources and set strict budget limitations. How well you use the existing resources can determine how soon you break even and start earning profits. Emerging technology solutions based on AI help you prioritize your processes to allocate resources accordingly. That way, you won’t spend excess money on unimportant tasks. Personalization for Enhanced User Experience Businesses are turning from a product-centric to a customer-centric approach

Surbhi kaushik
January 17, 2024
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Agile Business Development: Fostering Business Development Growth

At this moment in time, dynamic business environment, constant adaptation is not an option, it’s imperative for survival and growth. Managed Analytics Organizations (MAOs) face a critical choice: evolve or become obsolete. Agile Business Development (ABD) arises as the conductor, orchestrating a symphony of growth that empowers MAOs to navigate the dynamic market with resilience and achieve unprecedented growth. Leveraging a diverse portfolio of services, solutions, and contract-based resources encompassing the full spectrum of AI/ML, Data Science, Machine Learning, and Data Engineering organizations possess the unparalleled potential to harness the transformative power of Agile methodologies. Embracing ABD empowers MAOs with the agility to adapt and innovate seamlessly within the ever-shifting landscape of analytics. This dynamic approach enables continuous iteration, rapid response to market fluctuations, and a keen attentiveness to client feedback, in its entirety culminating in propelling business development to unprecedented heights. The inherent nimbleness of Agile practices equips MAOs with the capability to pivot strategies swiftly, refine service offerings with precision, and capitalize on emerging opportunities with laser focus. This holistic philosophy prioritizes continual learning, experimentation, and an unwavering commitment to customer-centricity, completely serving as the bedrock for sustainable and scalable growth. Ultimately, by integrating ABD into their core operations, MAOs navigate the complexities of the ever-evolving analytics industry and also flourish amidst its fluidity, achieving unparalleled growth and forging a path for continued innovation and excellence. From Monolith to Mosaic: Embracing the Power of Iteration ABD shatters the paradigm of rigid, linear strategies. It replaces them with a mosaic of iterative processes, allowing MAOs to adapt nimbly to market shifts, customer feedback, and unforeseen opportunities. This flexible approach eliminates the shackles of lengthy planning cycles, freeing MAOs to respond quickly and remain relevant in a rapidly evolving digital world. Flexibility Takes the Stage: A Collaborative Move of Agility ABD prioritizes flexibility, collaboration, and responsiveness. Rigid hierarchies are dissolved, paving the way for a flat, collaborative environment. Ideas flow freely, fostering innovation and allowing MAOs to pivot strategies, refine offerings, and seize fleeting opportunities. This collaborative move of agility ensures MAOs remain in exemplary rhythm with their customers, exceeding expectations and delivering exceptional value. Experimentation: The Fuel for Innovation’s Engine ABD is not a static state, but a journey of continuous learning and experimentation. MAOs are empowered to explore bold ideas, test their effectiveness, and learn from both successes and failures. This cycle of experimentation fuels innovation, propelling MAOs to the forefront of the industry and establishing them as thought leaders in the Managed Analytics space. Customer Centricity: The Unifying Melody ABD recognizes that the customer is the maestro of business growth. At the heart of ABD lies a deep commitment to customer-centric practices. This approach equips MAOs with the tools to gather meaningful customer insights, understand their evolving needs, and tailor their offerings suitably. By placing customer-centricity at the heart of their strategy, MAOs cultivate lasting relationships, build unwavering loyalty, and solidify their position as trusted partners in a competitive landscape. Adaptability: The Key to a Harmonious Representation The business landscape is a constantly evolving orchestra, where melodies shift and rhythms change. ABD equips MAOs with the agility to adapt to these changing dynamics. They can readily pivot strategies, re-evaluate value propositions, and embrace advanced technologies, ensuring they remain in an ideal tune with the market and continue to deliver exceptional value. ABD: A Transformation of Mindset and Measure Successfully implementing ABD is not merely adopting a methodology; it is a cultural transformation. Fostering a collaborative environment, encouraging receptive communication, and empowering teams to take ownership are the instruments that unleash the full potential of ABD. This shift in mindset allows MAOs to evolve into agile organizations, ready to seize opportunities and create a harmonious symphony of growth. Unleashing the Power of Agility By embracing ABD, MAOs embark on a transformative journey in the direction of sustainable and scalable growth. They become nimble, responsive, and customer-centric organizations, poised to lead the Managed Analytics landscape in the years to come. Stagnation is out, agility is in! Let’s turn up the volume and rock out to the rhythm of progress! Conclusion In conclusion, the union of Agile Business Development principles with the vast expertise of Managed Analytics Organizations paints a compelling vision of unparalleled potential and growth in the analytics landscape. By infusing agility, adaptability, and customer-centricity into their very core, MAOs become the vanguard of innovation, driving continuous evolution and transformation. From navigating the intricate terrain of AI/ML to embracing the power of Data Science, Machine Learning, and Data Engineering, the adoption of Agile methodologies transcends mere strategy to become a cultural beacon guiding their path to growth. With a commitment to perpetual learning, iterative refinement, and a steadfast dedication to client needs, MAOs chart a course for sustained and scalable growth. Through Agile Business Development, they can elevate their business acumen and redefine the standards of excellence within the industry, promising a future brimming with innovation, progress, and boundless possibilities.

Yashica Chopra
January 13, 2024
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5 Top Managed Analytics Companies in eCommerce- Trusted by India’s eCommerce Businesses

The Indian and global retail / eCommerce industry is rapidly changing to adopt the latest technologies. Many sellers and store owners can benefit from eCommerce analytics. Here, we’ll discuss the top five managed analytics companies in eCommerce industry and their offerings. eCommerce is a fast-growing industry around the world. It is also rapidly evolving, with many business owners and sellers adopting the latest technology, be it artificial intelligence, PoS (Point of Sale) software, or data science models to streamline sales and make effective decisions in real-time. Statista reports that the global retail eCommerce sales worldwide account for more than $6 trillion and have over 20% of the market share. Analytics are crucial for the eCommerce sector to overcome various challenges and reach out to the target audiences. From understanding demographics to analyzing customer feedback, data analytics supports e-commerce businesses to optimize their efforts and get improved results. According to Business Research Insights, the global eCommerce analytics market is expected to touch $56.16 billion by 2031 at a CAGR (compound annual growth rate) of 14.51%. The same report states that the adoption of 4G and 5G technology will boost eCommerce analytics and encourage more business owners to invest in managed analytics. In this blog, we’ll read more about e-commerce analytics solutions and the top companies to partner with for accessing managed analytics in real time. What is E-commerce Analytics? eCommerce analytics is the process of collecting, analyzing, and interpreting eCommerce data to derive actionable insights for decision-making. It helps in tracking and monitoring the KPIs (key performance indicators) to find effective ways to improve marketing, sales, and profits. Managed analytics for eCommerce is a third-party service provided by data analytics companies to help businesses unlock the full potential of their data and derive useful insights. The business doesn’t have to build an analytical model from scratch or make huge investments. Instead, it can partner with a service provider to implement business intelligence tools like Power BI and access the reports through customized dashboards. This is a quick, easy, and effective option to gain a competitive advantage and make data-driven decisions to boost the business. 5 Top Managed Analytics Companies in eCommerce Here’s a list of the top companies offering online retail BI solutions to various establishments from the eCommerce industry. Some service providers offer additional solutions for comprehensive digital transformation. DataToBiz DataToBiz is one of the top managed analytics companies in eCommerce, with years of experience working with businesses from the retail and eCommerce industry. The company has a presence in many industries with clients ranging from startups to large established brands. It uses advanced AI/ ML models, data science, and business intelligence tools like Power BI for eCommerce solutions. DataToBiz is a certified partner of Microsoft, Google, and AWS and has an expert team to build, deploy, implement, integrate, and upgrade managed analytical applications for the client. The company also provides tailor-made data warehousing services along with cloud computing and migration solutions. Businesses can use customized sales, marketing, financial, and inventory dashboards to track KPIs and make proactive decisions to grab market opportunities. The award-winning company is a one-stop solution for all eCommerce analytical needs. With transparent pricing, flexible partnerships, a diverse portfolio, and long-term support services, DataToBiz is a worthy choice for eCommerce businesses to adopt the data-driven model. Saras Analytics Saras Analytics is a unified data and analytics company for the eCommerce, retail, and DTC sectors. It offers bespoke solutions and supports sellers in utilizing AI, ML, and advanced analytics to derive precise real-time insights. As an eCommerce solutions company, it helps businesses derive maximum benefits from data through business intelligence, data visualization, data engineering, etc. Saras Analytics considers itself a team player and provides data team-as-a-service solutions for eCommerce and retail establishments to understand customer requirements, market trends, etc. The company increases customer experience and sales by streamlining business operations and optimizing resources. It aims to enable agile eCommerce decisions based on data-driven reports to minimize risk. Daton is a unified data platform developed by the company to facilitate the ease of global eCommerce services. The platform has over 200 connectors and provides eCommerce data insights to several clients. RetailNext RetailNext was the first in-store analytics platform built to help businesses from the eCommerce industry. The company’s products are trusted by many leading brands from several countries. The solutions are scalable and can be customized to suit the requirements of any business, irrespective of the number of stores in the network. The company provides a range of services to handle different aspects of the eCommerce business, such as store design, operations, merchandising, marketing, and asset protection. RetailNext has been developed by retailers to help modern sellers overcome different business challenges and achieve seamless results. Manage website traffic, online conversions, and more from an integrated platform. For example, Aurora is a next-gen sensor designed for physical location analytics. It uses a patented algorithm to combine deep learning and 3D imagery to deliver highly accurate results. The RetailNext solutions are pre-integrated to save time and can be easily implemented by all eCommerce businesses. Palantir Technologies Palantir Technologies was founded to make AI products for human-driven analysis of real-world data. The company is focused on creating the best user experience for businesses to work with data and derive actionable insights. It is among the top managed analytics companies in eCommerce that offer AI-powered solutions to streamline operations and decision-making. The company has developed different solutions to help business owners effectively manage operations, sales, customer experience, etc. For example, Gotham by Palantir Technologies is a commercial AI-ready operating system that accelerates decision-making for operators across different roles and departments. It is used by thousands of people and comes with multi-layered security. The built-in feedback loop trains and refines models used in the platform to ensure that it learns and trains itself to deliver better results over time. The company believes in offering full-stack interoperability through its platforms and gives the utmost importance to data security and data privacy. Streetbees Streetbees is an AI-based intelligence platform with top brands as clients. The eCommerce analytics company is disrupting market research by capturing real-life

Roshan Kumar
January 12, 2024
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Decoding Q*: A Comprehensive Exploration for Both Technical and Non-Technical Minds

Today, we’re on our journey to decoding Q* (Q-Star), a name that sparks interest and curiosity. But what’s behind this mysterious combination of letters and symbols? What This Blog Will Cover Dive into the origin of Q* (Q-Star) and its intriguing blend of Q-Learning and A* algorithms. Ready for an adventure at the crossroads of machine learning and pathfinding? Let’s embark on this exciting exploration together! Let’s Go… Fusion of Q-Learning and A-Star The name Q* (Q-Star) likely draws inspiration from two powerful algorithms: Q-Learning and A* (A-Star). Let’s break it down for both tech enthusiasts and novices alike! Q-Learning Unveiled Q-Learning is like teaching a pet new tricks but for computers! Here’s the gist: Environment and Agent: Picture a video game or maze as the environment, and the AI as your in-game character. In simpler terms, it’s like mastering a video game by learning and adapting over time! A* (A-Star) Magic A* is a wizard in finding the shortest path between two points. Imagine it as your GPS for optimal routes: Now that we’ve got the basics, let’s get a bit speculative. How do these algorithms fit into the realm of large language models and AI? Decoding Q* (Q-Star) for Language Models Current large language models (LLMs) have limitations, especially in creative problem-solving and long-term strategy. Here’s where Q* comes into play: In the language model landscape, Q* could revolutionize how AI learns from interactions, improving responses, and adapting to new information and feedback over time. Excitingly, OpenAI’s breakthrough in Q-learning might just usher in a new era for large language models, overcoming current limitations and paving the way for unprecedented advancements in AI. It’s a thrilling journey where machine learning meets pathfinding, potentially transforming how AI systems tackle complex tasks. And who knows, Q* might be the missing piece for the next big leap in AI evolution! What are your thoughts on Q* and its potential?

Yashica Chopra
January 09, 2024
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Top 10 AI Product Development Companies for Manufacturing

AI and ML solutions can revamp the manufacturing industry through real-time data analytics, IoT devices, digital twins, smart factories, and more. Here, we’ll discuss the role of AI and the top AI product development companies in manufacturing. Artificial intelligence is disrupting the manufacturing industry in many ways. Industry 4.0 promotes adopting technology in manufacturing to increase scalability, flexibility, agility, and production performance without spending more resources. Many manufacturers from around the globe have been investing in AI in some form or another. Artificial intelligence has a versatile role in the industry, from automation to robotics to predictive maintenance. Statistics show that AI can increase productivity by over 40% by 2035. A report by Markets and Markets says the global AI in the manufacturing market will reach $16.3 billion by 2027 at a CAGR (compound annual growth rate) of 47.9%. The global AI market size was valued at $196.63 billion in 2023 and is expected to reach $1811.8 billion by 2030 at a CAGR (compound annual growth rate) of 36.8%. Additionally, AI in manufacturing is useful in streamlining product development. Here, the term ‘product’ refers to the products manufactured by the enterprise as well as the software products companies develop to help manufacturers accelerate processes. Both can be achieved by partnering with AI product development companies and working together to gain a competitive edge in the market. AI Product Development in the Manufacturing Industry Artificial intelligence has brought significant changes to product development in the manufacturing sector. Manufacturers can be more innovative, creative, and flexible in developing new products. AI also reduces time-to-market and allows enterprises to release products quickly. From ideation to production to warehousing, distribution, and marketing, every step is supported by artificial intelligence. For example, machine learning in manufacturing can analyze large datasets and provide detailed reports. Manufacturers use these reports and insights to understand customer requirements, market trends, etc., to make data-driven decisions about product development. Since it can be cost-intensive to build AI models from scratch, enterprises opt for third-party (offshore, onshore, and nearshore) AI product development services by reputed companies. This bridges the talent, skill, and technology gap in the enterprise while ensuring the budget and timeline constraints are followed. Top AI Product Development Companies in Manufacturing DataToBiz DataToBiz is one of the leading AI/ML product development companies in manufacturing (and many other industries) with vast experience in building, developing, deploying, integrating, and customizing artificial intelligence models for enterprises. The AI product development company uses custom machine learning algorithms and advanced artificial intelligence tools to provide seamless product development and integration services. It helps manufacturers boost efficiency, use data analytical reports for insights, and personalize products based on customer feedback and market trends. The tried and tested six-step AI product development process ensures the promised results are delivered to the clients. Since the company provides long-term maintenance and upgrade services, manufacturers can become successful industry leaders. DataToBiz offers comprehensive end-to-end solutions, starting from ideation to long-term maintenance. The award-winning company takes care of data engineering, AI/ ML development, cloud computing, big data analytics, generative AI, data visualization, data engineering, and many more. It focuses on helping clients align their business vision and goals with market requirements to gain a competitive edge and steadily increase revenue over the years. DataToBiz has flexible and transparent pricing suitable for MSMEs, emerging enterprises, and large-scale manufacturers from around the globe. LeewayHertz LeewayHertz is a software development company offering tailor-made digital solutions to global clients. The company has a close-knit team of AI and Web3 developers who create next-gen apps to help businesses overcome challenges and achieve their goals. It works with startups, scale-ups, and enterprises to help them become tech-savvy and take advantage of AI products to boost their business. LeewayHertz offers custom manufacturing software product development for automation, production planning, and remote asset management. The company combines technologies like blockchain and IoT (Internet of Things) for manufacturers to reduce operational costs without compromising quality. It provides an array of services as required by enterprises. Cognizant Cognizant is a multinational company with over twenty-five years of experience. It is also among the top AI manufacturing development companies that help enterprises transform their business models and reimagine processes using the latest technology. From modernizing legacy systems to converting insights into action, the company provides a plethora of services to businesses. Cognizant removes the barriers to innovation by integrating manufacturing processes with AI/ ML technologies. It promotes the use of IoT (Internet of Things) and generative AI for automation, real-time analytics, and more. The company helps enterprises build smart factories to transform traditional manufacturing into agile and future-ready methods. The company also helps clients improve sustainability and gives high importance to green practices. Markovate Markovate specializes in offering AI and customized digital solutions to help businesses use technology to gain strategic advantage, enhance performance, promote change, and achieve goals. The company works with enterprises from the manufacturing industry to help them embrace world-class digital experiences through cutting-edge technologies. It designs ML frameworks and data analytical tools for scalability, reliability, and optimum performance. Markovate uses generative AI, adaptive AI, and other advanced technologies to help manufacturers transform their vision into reality. From boosting productivity to increasing overall quality, the company supports enterprises at every stage and enables seamless adoption of AI and ML applications. It offers web and mobile application development, cloud computing services, and other solutions necessary for manufacturers to digitally transform their processes. Builder AI Builder.AI is an AI product development agency that offers bespoke solutions to clients from different industries. It doesn’t believe in off-the-shelf apps, which may or may not be suitable for a business. The company has built award-winning apps and raised around $450 million to unlock the power of technology and enhance its role in boosting human potential. It has developed diagnostic software for the automotive industry to use real-time analytics for decision-making. Builder.AI also builds CRM applications, OMS (order management systems), inventory management software, etc., to streamline various manufacturing processes. It helps automate recurring tasks to save time and resources and reduce operational costs. The company promotes AI product development

Kavika Roy
January 09, 2024
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Leveraging Large Language Models in Healthcare

Explore the potential of (LLMs) Large Language Models in healthcare, their applications, challenges, and prospects for improved diagnostics and patient care. Artificial Intelligence (AI) has ushered in a new era of possibilities, and at the forefront of this technological revolution are Language Models (LLMs). These powerful AI systems, equipped with deep learning algorithms, have the remarkable ability to understand, generate, and manipulate human language on an unprecedented scale. As we explore the potential of these models, we’ll delve into their applications, the challenges they bring, and the promising future they hold for advancing diagnostics and patient care. In recent years, the field of artificial intelligence (AI) has witnessed a revolutionary advancement with the emergence of Large Language Models (LLMs). With 30% of the world’s data volume being attributed to the healthcare industry, there exists a significant potential to harness the power of Large Language Models (LLMs) to operationalize and deliver new insights. These sophisticated AI systems, powered by deep learning algorithms, possess the ability to comprehend, generate, and manipulate human language at an astonishing scale. While their applications span various domains, the significance of Large Language Models in healthcare and clinical trials is particularly noteworthy. In this article, we delve into the realm of LLMs and their profound impact on the healthcare landscape, exploring their capabilities, applications, challenges, and future potential. Understanding Large Language Models At the core of this technological breakthrough lies the concept of Large Language Models. These models are intricate neural networks that have been meticulously trained on massive datasets containing diverse textual information. The training process equips them with the capacity to understand the nuances of language, context, and semantics, enabling them to perform tasks that were once considered exclusive to human intelligence. Unlike traditional language processing methods that rely heavily on rule-based approaches, LLMs rely on data-driven learning. This data-centric approach enables them to capture intricate language nuances and adapt to the ever-evolving dynamics of human communication. The shift from predefined rules to learned patterns marks a pivotal advancement in natural language understanding and generation. LLMs undergo training using vast datasets and employ self-supervised learning to predict the subsequent token in a sentence, taking into account the context around it. This iterative process continues until the model achieves a satisfactory level of accuracy. LLMs can be fine-tuned to perform a wide array of Natural Language Processing (NLP) tasks, such as: Creating interactive chatbots like ChatGPT. ● Generating text for purposes such as product descriptions, blog entries, and articles. ● Providing answers to frequently asked questions (FAQs) and directing customer queries to appropriate human support. ● Analyzing customer feedback found in emails, social media posts, and product reviews. ● Converting business content into various languages through translation. ● Sorting and categorizing extensive text data to streamline processing and analysis. Examples of Large Scale Language Models Three prominent examples of Large Scale Language Models are GPT-4, BERT, and T5. GPT-4, developed by OpenAI, is renowned for its creativity in generating coherent and contextually fitting responses. BARD on the other hand, developed by Google, revolutionized language understanding by considering the full context of a word within a sentence rather than processing words in isolation. T5, short for “Text-to-Text Transfer Transformer,” excels in various language tasks by treating them as text-to-text problems, demonstrating the adaptability of Large Scale Language Models. Applications of Large Language Models in Healthcare The integration of Large Language Models in healthcare has opened up a multitude of possibilities, transforming various aspects of healthcare delivery and research. Clinical Documentation and EHRs Efficient and accurate clinical documentation is essential for patient care. LLMs have the potential to automate the process of transcribing medical notes, generating detailed patient records directly from spoken or written input. This not only saves time for healthcare providers but also reduces the risk of errors in patient data. Literature Review and Knowledge Extraction The abundance of medical literature presents a challenge in staying updated with the latest advancements. Large Language Models can expedite literature reviews by summarizing articles, extracting key insights, and identifying relevant studies. This aids researchers, clinicians, and medical professionals in staying informed and making evidence-based decisions. Patient-Provider Communication Enhancement Effective communication between patients and healthcare providers is paramount. LLMs can assist in crafting personalized and comprehensible explanations of medical conditions, treatments, and procedures. This bridges the knowledge gap, enabling patients to make informed decisions about their health. Drug Discovery and Development The drug discovery process is complex and time-consuming. Large Language Models can aid in sifting through vast amounts of biomedical data to identify potential drug candidates, predict drug interactions, and assist in the design of clinical trials. This accelerates the drug development pipeline and enhances precision medicine. Clinical Trial Design and Execution Designing and conducting clinical trials requires meticulous planning. LLMs can contribute by analyzing existing trial data, predicting patient recruitment rates, and optimizing trial protocols. These insights facilitate efficient trial design and execution, leading to quicker and more cost-effective outcomes. Large Language Models Encoding Clinical Knowledge Enriching Large Language Models with domain-specific medical knowledge is a pivotal step in their healthcare applications. This involves training the models on vast medical datasets, encompassing information from electronic health records, medical textbooks, research articles, and clinical guidelines. The integration of medical expertise enhances the models’ ability to generate contextually relevant and accurate medical content. While imbuing LLMs with medical knowledge is promising, challenges arise due to the dynamic nature of medical science. Keeping the models updated with the latest research, ensuring accuracy, and addressing biases in medical data are ongoing concerns. Additionally, the inclusion of sensitive patient information demands robust data privacy measures. Pre-trained medical Large Language Models provide a foundation for various healthcare applications. These models arrive equipped with a baseline understanding of medical language, reducing the need for extensive training. By leveraging pre-existing medical knowledge, developers can focus on fine-tuning the models for specific tasks, streamlining the implementation process. Working Mechanism of Large Language Models Pre-training and Fine-tuning Process The proficiency of Large Language Models stems from a

Kavika Roy
January 08, 2024
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DataToBiz’s AI Solutions Pioneering the Path to Intelligent Automation

Emerging as a go-to partner for enterprises aiming to embrace the advancements in AI, DataToBiz acknowledges its immense potential and has curated a diverse range of AI solutions to cater to various business needs. “AI is the enigmatic force that blurs the line between imagination and possibilities, and we help businesses turn these exact possibilities into realities,” says Ankush Sharma, Co-Founder, and CEO, DataToBiz. DataToBiz, a leading AI solutions provider, empowers organizations with advanced artificial intelligence technologies, driving unparalleled efficiency, productivity, and innovation. Over time, the company is emerging as a critical driver for organizations looking to streamline processes, enhance decision-making, and unlock new business opportunities. DataToBiz recognizes the immense potential of AI in transforming industries and has developed a range of AI solutions that address diverse business needs. AI Solutions : Pioneering Intelligent Automation DataToBiz understands the competitive business landscape and acknowledges the significance of harnessing the power of AI into it. By providing customized AI solutions, DataToBiz empowers companies to unlock valuable insights from their data, enabling them to make informed decisions and drive innovation. Leveraging AI, their offerings encompass machine learning, in-app development, predictive modeling, and natural language processing, providing a path forward for their corporate partners. With a keen focus on SMBs, SMEs, and large enterprises across various industries, DataToBiz has established itself as a trusted AI consultant, or better- a partner. Renowned market players such as Dentsu, Tosoh Quartz, TransSIGHT, FTCSolar, Nordex, and more have implemented their advanced data solutions. At the core of their solutions lie advanced ML algorithms capable of analyzing vast volumes of data to unveil hidden patterns, trends, and insights. These algorithms continually and systematically learn from data, empowering businesses to make accurate and efficient data-driven decisions. Also, the expertise in natural language processing (NLP) is another critical aspect of their AI solutions. By leveraging cutting-edge NLP models, organizations can automate language-related tasks like sentiment analysis, content generation, and understanding. This automation saves time, and resources, and enhances customer experiences and engagement. DataToBiz- A Seal of Trust After recently completing a milestone of over 5 years in the industry, DataToBiz has found its place as one of the leading AI powerhouses sealed with the trust of various enterprises, in multiple industries around the world. With a proven track record of delivering innovative AI solutions, their expertise continues to drive technological advancements and reshape business landscapes. Along with featuring on Govt of India and MeitY, DataToBiz has proudly held the distinction of being Clutch’s top-ranked artificial intelligence company in India consistently for 3 years now. Not only this, with a user base of over 5.5k+ people around the world, DataToBiz has 2 in-house AI offerings: PrepAI, an advanced AI-based exam generator, and HirelakeAI, a turnkey AI-backed hiring solution. The Future Representation In a world where artificial intelligence is shaping the future of industries, DataToBiz stands as a trusted partner, delivering cutting-edge AI solutions that enable organizations to thrive in the era of intelligent automation. As the go-to choice for enterprises seeking AI advancements, DataToBiz is shaping the future representation of AI in business, creating a pathway toward transformative growth and success. Originally Published on Benzinga