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LLMs in AI Development- Key to AI’s Next Breakthrough?

Large language models can provide a transformative experience in various sectors, be it real estate, healthcare, entertainment, or manufacturing. Here, we’ll discuss the future of LLMs in AI development and how it can help businesses enhance their processes, products, and services.  Artificial intelligence has seen great advancements in recent years. It is a part of everyday life, be it social or professional. From smartphones and voice assistants to commercial chatbots, content generators, and workflow automation tools, AI has diverse applications and uses. According to Grand View Research, the global AI market is estimated to touch $1,811.8 billion by 2030.  Large Language Models (LLMs) are a part of artificial intelligence and play a vital role in generative AI. These have shot to fame with the success of ChatGPT and other generative AI tools (generative AI apps and built on LLMs and other foundation models, so LLM is a part of generative AI and not GenAI on the whole). Statistics show that the global LLM market was $159.0 million in 2023 and is expected to grow at a CAGR (compound annual growth rate) of 79.80% to reach $259.8 million in 2030. It is predicted that 750 million applications will use LLMs by 2025 to automate 50% of digital work. In this blog, we’ll talk about what LLM stands for in AI, their working methodology, and the possible future of LLMs in AI development. What are LLMs in AI Development? Large Language Models(LLMs) are used to build generative AI applications for various purposes. So, is ChatGPT LLM? Yes, ChatGPT comes under LLMs, but it is actually a GenAI tool.  LLMs are massive deep learning models pre-trained on huge amounts of data to provide better quality output by understanding the context of the user’s input. The large language models have powerful transformers, which are a set of neural networks with encoders and decoders that can analyze the input data to interpret the meaning and provide a relevant and (relatively) accurate output.  LLMs can handle unsupervised data and work with hundreds of parameters, which makes them highly suited for handling complex tasks. They are versatile, flexible, and customizable. For example, LLMs can support generative AI tools that convert input text into images, videos, or audio sounds. It can scan, read, edit, and summarize several pages of text in a few minutes. This makes LLMs an important part of AI product development.  As per the Datanami August 2023 Survey, 58% of companies work with LLMs but a majority of them are only experimenting with it. This shows that even though large language models are gaining popularity, businesses taking time to explore the technology and understand how it can help their establishments. The diverse role of LLMs in AI development makes it clear that the models will have a profound impact on the future. Future of LLMs in AI Development  AI researchers want to build culturally and linguistically diverse and inclusive LLMs to make the models user-friendly for people around the world.  Predicting Next-Gen AI-Language Models LLMs in AI language models can help in providing more human-like interactions with chatbots. The LLMs can power AI chatbot solutions to be more context-aware and learn from the interactions with users to offer better responses. Additionally, it could also make AI more capable of understanding the subtle nuances in text. This can make the language models more efficient and accurate for a wide range of communication purposes. Cross-Disciplinary Usage  What if we say, LLM in AI development can promote the integration of two or more technologies for developing applications for different fields? For example, AI language models can be integrated with robotics or computer vision to build robots that understand verbal instructions and respond more effectively to human interactions. Another example of cross-disciplinary application is how the LLMs can help AI tools simultaneously analyze visual and auditory data for enhanced security and surveillance.  Breakthrough in Algorithms Large language models can streamline AI algorithms to enable the models to process more data in less time and with fewer resources. This reduces response times and empowers the models to offer better real-time capabilities. It could lead to AI applications that minimize energy consumption while optimizing user experiences. Businesses can redefine their processes to make AI an integral part of their establishment and get enhanced results. Apps with Greater Efficiency  AI-powered innovation strategies that actively use LLMs in AI development will result in applications that are not only bigger but also more efficient and diverse in handling a plethora of tasks. For example, the larger models could work even on smaller devices (like smartphones) which will enable users to work on the go.  Addressing Ethical and Bias Concerns  Ethical concerns and bias are two major challenges faced when adopting LLMs in a business. However, in the future, the same models could help overcome these concerns. AI researchers and developers are working on building models that can detect and mitigate bias in data. They are also focusing on developing LLMs that can be used ethically. While this could take some time, it is definitely something to look forward to in the future.  Generating Personalized Content  LLM advancements can further help AI tools to personalize content for various purposes like articles, news snippets, listicles, ads, target marketing, etc. Though there are already applications that offer such services, the content still feels like it is written by a machine. In the future, the LLMs used in AI development will understand the intricacies of language better to create text that aligns with the user’s requirements and read as if it has been created by humans.  Domain-Specific Applications  While businesses from different industries can use many large language models, future models can cater to specific domains. For example, AI developers can build LLMs for healthcare (patient management), finance (streamline payments and detect fraudulent transactions), law (read the reports and summarize them without misinterpretations), etc. Such models can be highly advantageous for businesses as they are trained on data from the industry and give more accurate results.  Real-Time Query

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Why Contract Staffing is the New Normal in IT?

IT contract staffing is transforming the future of work by offering flexibility, access to specialized talent, and cost efficiency. It allows companies to quickly adapt to changing project needs while workers enjoy varied experiences and work-life balance. This model is essential for meeting modern IT challenges and achieving business success. Hiring in the field of technology has its challenges, especially for top or highly specialized positions. Here, hiring is a simple factor since it calls for the selection of talented individuals. But engineering jobs are some of the hardest to fill in the current job market, taking an average of 49 days to hire. But here’s a more interesting fact: Each vacancy costs roughly $33,251 per annum, and expenses can soar to hundreds or thousands of dollars while waiting for the dream candidate.  Therefore, what can companies do to fast-track the process of finding the right talent? Some employ individuals without the right qualifications, which can result in major losses to the companies in the long run. However, others address the issue right from the beginning by opting for a flexible solution. It is also commonly referred to as IT contract staffing or IT recruitment. The first strategy is a short-term strategy that involves identifying talent and getting them into the organization as soon as possible; the second strategy seeks to identify talent for permanent positions within the organization. Read on to learn about this staffing model, its benefits, legal compliance, and so on. What is Contract Staffing? Contract staffing is a model whereby organizations employ their employees under fixed-term contracts rather than permanent employment. This modality is so popular because it is inexpensive and easy to control, and organizational leaders can easily access the right talent when it is needed. IT contracting is also much more favorable for many workers as it provides more flexibility and is usually paid better. Furthermore, such contracts can also be temporary but offer the option to turn them into a fixed-term contract for the employee’s advantage and their employer’s benefit. A recent market report estimated that the world market for IT staff augmentation would increase by 3.66% by 2029. Types of IT Contract Staffing There are four main types of IT contract staffing: Steps to Follow in the IT Contract Staffing Process IT contract staffing is a powerful strategy for organizations needing extra support for their team. By following these steps, you can ensure a smooth process and successful delivery of quality IT solutions. 1. Identify Your Needs and Requirements First, determine what specific skills or expertise your project requires. Whether you’re launching a new software development project, handling a system upgrade, or managing a sudden workload spike, knowing where your team might need a boost is essential. Once you’ve established the need, define the exact skills, experience, and qualifications required to ensure that the contracted IT professional is the right fit. 2. Rely on Specialized IT Staffing Agencies Realize your need to see how the right IT professionals may be secured. You have two main options: Staffing Agencies: Many MNCs still hire IT staffing companies that deal with the contractual employment of IT professionals. These agencies make work easier by generating a list of qualified candidates who have undergone standard screenings. Recruitment outsourcing firms assume the tasks of the first levels of recruitment, such as search and selection. Direct Recruitment: If you want to coordinate the entire procedure independently, then recruitment can be done on your own. This includes advertising for the position available, sorting through the pile of applicants, making a list of those candidates who will be offered an interview, and even the interviewing process and hiring of the candidate all by yourself. 3. Contract Negotiation So, if you have tapped the right candidate, there is no better time to negotiate than the IT contracting provisions. Here’s what typically gets covered: 4. Build an Onboarding Process After finalizing the contract, the next step is onboarding the IT professional. This involves introducing them to your company’s policies, project goals, and team dynamics to ensure they fit seamlessly into your workflow. Here’s what effective IT contract staffing usually includes: 5. Project Execution and Evaluation Once onboarding is complete, the technology contract staffing can start contributing to the project. They’ll work within the agreed-upon timeline, meeting milestones and objectives. Monitoring their performance throughout the contract is crucial to ensure they’re meeting expectations and delivering quality work. How Can IT Contract Staffing Propel Your Business Forward? IT contract staff may be recruited to provide narrow technical skills for certain engagements; this gives businesses the flexibility to respond to the dynamic needs of an organization while making it cost-effective. Here’s how: Flexible Staffing One of the benefits of IT contract staffing is that it is very flexible. Employers can easily hire a lot of workers or few workers depending on the projects at hand without necessarily having to contract the workers’ employment. This has made it possible for companies to manage change and be able to respond to any conditions that arise promptly. Access to Specialized Talent Specialized or right technical skills are difficult to find, as stated by employers from IT and technology. 77% of employers find it difficult to find talent in the field of technology. IT staffing services minimize this risk by providing businesses with a wider talent pool, helping to ensure that the right talent is hired. Cost-Efficiency IT outsourcing also opens new opportunities to rationalize labor costs. Compared to full-time employees who require the provision of benefits, stock options, and other employee privileges, contract professionals are only paid for the duration of their project. Meets Immediate Business Needs Contract IT professionals are usually willing to go to work immediately and start producing; hence there, little time is spent on training and incorporating them into ongoing projects. This ease in the establishment of the workforce is particularly helpful for those organizations with short working time frames or received an unexpected influx of work. Future Trends of IT Contract Staffing The

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Top 10 Reasons to Prioritize Data Warehousing Services

Data warehousing is like building an organized library for datasets in your organization. It integrates data from various sources, improves data quality, and makes it easy to analyze and make smart decisions upon it. Investing in data warehousing services ensures you can make well-informed decisions that keep you ahead of the competition. As decision-making moves towards relying on data and analytics, the demand for data solutions has increased. Incidentally, 31% of respondents are eager to quickly scale up their analytics spend to support more users and handle bigger data. Additionally, 28% are aiming to focus on improvement in the infrastructure which would support the cloud, on-premise as well and regional computing. But how can you efficiently handle petabytes of data? The answer is the data warehouse.  Data warehouses are a kind of central repositories designed for storing and processing huge quantities of information from various segments of an organization. When approaching the question of investing money in data warehousing services, you should be acquainted with what gets you the maximal profit. In this blog, let’s try to break down what is important to know but might be too obvious to think of when getting started with data warehousing services. But first, let’s start with the basics. What is a Data Warehouse? A data warehouse, often called an enterprise data warehouse (EDW), is a central system where businesses keep important information like customer and sales data. This information is stored for analysis and reporting. Data warehouses are essential for generating insights and supporting decision-making through business intelligence (BI). They typically hold both current and historical data that has been collected, transformed, and loaded (ETL) from various sources, including internal and external databases.  Essentially, a data warehouse serves as a business’s single source of truth (SSOT) by consolidating data into a stable, standardized system that relevant employees can easily access. These systems are designed for online analytical processing (OLAP) and enable fast, efficient analysis of data from multiple angles. Data warehouses can store vast amounts of summarized data, sometimes reaching several petabytes. Why Should You Have a Data Warehouse? The main benefit of a data warehouse is that it brings together data from various sources into a unified format. This consistency ensures that the data is accurate, leading to well-informed decisions. When data is standardized across the business, every department can generate consistent and reliable results. Traditionally, data warehouses were located on servers within a company’s premises (on-premise). However, nowadays, many data warehouses have moved to the cloud, where they can store and analyze vast data sets. Some popular cloud-based data warehousing platforms include: Data warehousing services often serve as a single, reliable source of truth for businesses, centralizing big data in a secure, stable, and standardized system that’s accessible to the right teams and employees. Reasons To Invest in Data Warehousing Services It is important for an organization that requires information in real time to make the right decisions to use a data warehouse. Still, these reasons can help you determine whether, in your case, data warehousing services are worth the investment. 1. Unlock Data-Driven Potential Decisions are no longer hove on guesswork or instinct – at least they shouldn’t be. Indeed the modern-day leader has the great fortune of having a basis for decision making informed by current data and this is made possible through a data warehouse. For information power to be realized optimally, there must be a loss of data ownership where one department usually owns most of the data. A data warehouse can rectify this scenario, and those in need of some specific details do not need to go through all sorts of hoops or even other departments. When it is set up as a single source organizing all other material, data warehousing services ensure that information seekers are well-equipped to find what they require and use it decisively to chart the destiny of the organization. 2. Harness the Power of Automation Data warehousing services open up opportunities for businesses to explore automation. Automating different parts of operations is gaining traction, especially as people see how it can help avoid costly errors and speed up processes. Market studies suggest that the global industrial automation market could reach $265 billion by 2025, a significant jump from $175 billion in 2020. Data warehouses play a crucial role in supporting these automation efforts. Businesses can use software-driven workflows to automate tasks like data access and transfer, reducing the time needed to gather information for auditors, investors, or other stakeholders. Automation can also speed up data analysis, helping uncover insights much faster. Additionally, it’s possible to automate error detection and logging, making it easier to spot potential issues and address them quickly. By understanding how data warehousing services are used within an organization, businesses can identify the best areas to implement automation. 3. Keep Your Data Secure When data is scattered across multiple locations, makes your security more challenging. Many leaders don’t even know how much data they have or where it’s stored. With data warehousing services, everything is stored in one place, making it easier to track and secure information. Plus, most data warehousing platforms come with built-in security features. Some can block harmful SQL code from outside attacks, while others limit how much data someone can view at once, reducing the risk of unauthorized use. Organizations can also control who accesses the data warehouse and why. This ensures that people only see what’s relevant to their job. Additionally, some data warehouses lock out users who try to log in from unusual locations, making it harder for hackers to take advantage. To effectively implement data warehousing services in your company, it is advisable to leverage digital transformation consulting services for a well-guided and strategic implementation. 4. Enhance Data Quality and Consistency Sustaining high quality and consistency of the data is an essential requirement for your organization. Worse the cloud data is unstructured or inaccurate and hence will not be of much use. A data warehousing system can aid in

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AI as a Service Companies in Manufacturing – 10 Top Players

Industry 4.0 and smart manufacturing are not possible with artificial intelligence. AI offers numerous benefits for manufacturers. Here, we’ll discuss the top ten AI as a Service companies in the manufacturing industry and the benefits of using AI in enterprises.  With artificial intelligence becoming a part of every industry, it’s no surprise that it has a vital role in manufacturing. According to Meticulous Research, AI in manufacturing market is predicted to reach $84.5 billion by 2031 with a CAGR (compound annual growth rate) of 32.6% between 2024 and 2031. Meanwhile, the global AI market is estimated to be $1,811.8 billion by 2030.  Additionally, technological advancements have led to AI being offered as a cloud service. This is popularly known as AI as a Service (AIaaS). While Microsoft, Google, and Amazon (AWS) have the largest market share in this sector, many third-party companies offer AI as a service to manufacturers from different niches (automotive, aerospace, electrical, chemical, etc.). Partnering with the right AI product development company helps an enterprise seamlessly adopt smart manufacturing practices and gain an edge in competitive markets.  In this blog, we’ll read more about the role of artificial intelligence in manufacturing and the top ten companies offering AIaaS solutions to manufacturers. How Does AI as a Service Bring Efficiency in Manufacturing? The application of AI in manufacturing is diverse, varied, and innovative. Artificial intelligence can improve efficiency in manufacturing by automating repetitive tasks, enhancing quality control standards, shortening the production cycle, increasing supply chain visibility, reducing resource consumption, and making it easier to scale production according to market demand. AI can also make enterprises energy-efficient by identifying areas to reduce wastage. Data-driven decision-making based on insights derived from advanced analytics helps the top management navigate the complex and volatile markets in different countries.  Manufacturers don’t have to build the AI models from scratch or spend millions of dollars on developing applications in-house. AIaaS companies offer access to advanced tools and technology through cloud systems. Enterprises can migrate their processes to cloud servers and rely on the cloud IT infrastructure to streamline their internal operations. AIaaS is a cost-effective alternative for manufacturing businesses to adopt artificial intelligence.  So, what companies are providing AI services? Let’s check them out below!  10 Top Players Offering AI as a Service in Manufacturing DataToBiz DataToBiz is an AI-as-a-service company offering AI, ML, BI, data engineering, and cloud transformation solutions to MSMEs, SMBs, startups, and large enterprises. It has a strong presence in manufacturing, supply chain, transportation, and several other industries. The company’s tailored services for AI in manufacturing can help with strategy creation, product design and development, streamlining the supply chain, integrating cloud systems, connecting with IoT (Internet of Things) devices, setting up personalized dashboards, and aligning business processes with long-term objectives. The company follows a six-step approach to increase flexibility, scalability, and sustainability for clients. DataToBiz has won several awards for providing customer-centric end-to-end AI services to manufacturers from different parts of the world.  Glassdoor Rating: 4.8 Stars  IBM IBM is a popular multinational company offering AI consulting services for small, medium, and large enterprises from manufacturing, IT, and other industries. The company combines AI and hybrid technologies to help enterprises become more agile and scalable. IBM Watson’s platform is customized and deployed in manufacturing units to help clients unlock the true potential of business data and make data-driven decisions. It empowers businesses to become more aware of the market threats and opportunities. Additionally, IBM has many tools like Cloud Pak, Maximo, Supply Chain Intelligence Suite, etc., which can be integrated with the existing processes to deliver actionable insights and streamline internal operations in an enterprise.  The company assists clients in turning sustainability goals into tangible actions.  Glassdoor Rating: 4.0 Stars  Siemens Siemens is a global service provider with a presence in manufacturing, automotive, telecommunications, and other industries. The company has developed industrial AI solutions for large enterprises to adopt advanced technologies into their business. It is one of the leading examples of companies that offer AI as a service to clients from various regions. The AI services empower enterprises to standardize their processes, integrate machine learning algorithms, and streamline data and security requirements. The company develops a comprehensive AI framework for manufacturers to begin their Industry 4.0 journey and embrace smart manufacturing. Siemens follows a closed-loop model which includes all steps from planning to upgrading. The cycle is continuous and always active so that manufacturers can achieve their goals.  Glassdoor Rating: 4.2 Stars  C3.AI C3.ai is an enterprise AI service provider accelerating digital transformation in industries like manufacturing, defense, transportation, oil & gas, etc. The company’s AI development services address the key roadblocks and challenges in the manufacturing industry and help enterprises overcome the issues to become successful. Its C3 AI platform can be integrated with third-party apps to help manufacturers collect data from multiple sources, analyze the datasets, and derive meaningful insights for effective decision-making. The company offers extra tools for inventory optimization, supply chain risk assessment, transportation management, and more. The enterprise AI platform is 25 times faster and just as easy to use. From energy management to CRM, manufacturers can enhance all their operations by partnering with C3.ai.  Glassdoor Rating: 3.3 Stars  GE Vernova GE (General Electric) is a group of companies catering to the diverse needs of enterprises in the manufacturing, aerospace, and healthcare industries. GE Vernova is an AI platform developed for manufacturers to streamline their energy consumption and become a sustainable business. It focuses on ESG reporting and helps enterprises accelerate their adoption of reliable, sustainable, and affordable energy while enhancing customer experience and improving the quality of life for employees. The platform’s focus is on reducing the carbon intensity of the enterprises without compromising their access to advanced technology like, AI, ML, business intelligence, etc. GE works to empower the next generation of manufacturers to dream bigger, better, and bolder. The company has over 130 years of experience in the market.  Glassdoor Rating: 4.0 Stars  Rockwell Automation Rockwell Automation offers AI as

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IT Staff Augmentation Services for B2B Enterprises – Top 11 Market Players

Information technology is for everyone. Businesses can hire a talented team to achieve their IT goals. Here, we’ll discuss the top 11 IT staff augmentation services companies for B2B enterprises and the process of building an external team of experts to work with your business.  B2B or business-to-business is a model where a transaction occurs between two businesses, such as a manufacturer and a supplier, the manufacturer and a distributor, an IT company and its application providers, etc. B2B enterprises are business entities that primarily cater to other businesses. They may or may not offer products and services to general consumers. The changing demands in the global market have made many companies revamp their working models. Whether adopting new technologies, automating workflows, remote teams, or collaborations between internal and external employees, B2B enterprises have been streamlining their processes in recent times.  This led to an increase in demand for IT staff augmentation services. Instead of hiring employees on the payroll, enterprises collaborate with staff augmentation providers to build a team of experts in less than a week and complete a project in a short time. Statistics show that the global staff augmentation market size is likely to reach $145.12 billion by 2027, while the IT staff augmentation market is estimated to have a CAGR (compound annual growth rate) of 6.01% between 2020 and 2027.  In this blog, we’ll read more about IT staff augmentation and the top eleven service providers for B2B enterprises to strengthen their workforce temporarily and whenever necessary.  What is the Process Behind IT Staff Augmentation Services in B2B? Typically, IT staff augmentation services are a part of the umbrella term outsourcing. In staff augmentation, a business builds a temporary team of professionals by hiring from the service provider. The team works with the business as per the agreement. Once the project is complete, the team is dissolved. The business pays for its expertise by choosing a suitable package offered by the service provider. This could be hourly payments, project-based payments, etc. The duration also depends on what the business wants.  The process of hiring an IT staff augmentation team is usually mentioned on the staff augmentation services websites belonging to the service providers. This can change from one company to another. However, the following are the steps in the B2B staffing process.  This could be an in-house team or a remote team (even a combination of both). Similarly, the external team may or may not interact with the existing business employees. Once the project is complete and the agreement’s terms are met, the team is dissolved. A team can be formed whenever the business needs additional employees and doesn’t want to hire them permanently.  IT Staff Augmentation Services for B2B Enterprises- Top Market Players! DataToBiz DataToBiz is one of the leading AI, business intelligence, and data analytics staff augmentation firms in the market. The award-winning company has experienced, efficient, and friendly IT professionals from diverse domains. It offers nearshore and offshore IT staff augmentation services for clients from several industries. Businesses can hire data scientists for B2B projects through hourly-based, project-based, dedicated teams, or full-time hiring packages. The company partners with most businesses, be it a startup or a large enterprise. Moreover, it offers cost-effective pricing and tailored solutions for each client. Businesses can use the staff augmentation estimator tool to get a quote. DataToBiz believes in scalability, flexibility, transparency, and clear communication. The teams promise to deliver the expected results as per the schedule.  Clutch Rating: 4.8 Stars  eLuminous Technologies eLuminous Technologies is a custom web and mobile app development company offering IT staff augmentation services to B2B and B2C enterprises. The company has a presence in many industries and helps clients enhance their tech capabilities by hiring experts for various IT projects. It has short-term teams, conventional team augmentation, managed recruitment, long-term staffing, complete project outsourcing, and tailored IT staff augmentation models. Businesses can choose the most suitable model based on their requirements and budget. eLuminous Technologies follows a strict NDA policy and provides a dedicated project manager for each client, along with more add-on options. From app development to business intelligence, it covers many domains in the IT industry.  Clutch Rating: 4.7 Stars  Techahead Techahead is among the top IT staff augmentation providers in the industry and a one-stop solution for various tech services. The company handles many on-demand IT staff augmentation requirements by offering flexible and scalable teams for clients. It has experience in industries like healthcare, financial services, and eCommerce and has enough awards to prove its worth. The company specializes in customized staffing solutions and gives great importance to team compatibility as it affects the results. It also provides stringent security measures to ensure the project details are kept confidential. Techahead follows a six-step IT staff augmentation process that includes post-project support and continuous development solutions.  Clutch Rating: 4.8 Stars  Bacancy Technology  Bacancy Technologies is one of the top software development companies offering IT staff augmentation services to fill the resource gap in B2B enterprises and provide the necessary tech expertise. From UI/ UX testing to DevOps, AI/ ML engineering, etc., the company has IT teams for various project requirements. It has over a thousand and fifty agile developers working with clients from different industries. The company also offers dedicated teams, managed IT services, and full project outsourcing. Bacancy Technology has monthly and hourly pricing models for IT staff augmentation services. Businesses can also get a fixed quote for large and long-term staffing requirements. The company has a 15-day risk-free trial to onboard a developer into an existing team.  Clutch Rating: 4.7 Stars  Techminds Group  Techminds Group is a global and one of the top IT staff augmentation companies offering ISO and CMM-certified solutions to businesses from around the world. The company provides experienced and certified tech professionals to empower the existing teams of its clients and help them achieve their business objectives. B2B enterprises from many industries can choose from different staff augmentation models like contract (temporary), contract

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21 Biggest Cloud Transformation Trends in 2025

With more organizations migrating their IT infrastructure to the cloud platforms, it is vital to understand what it means and how cloud transformation can help a business. Here, we’ll discuss the biggest cloud transformation trends in 2025.  Many organizations of various sizes are investing in cloud transformation solutions to revamp their business processes and benefit from cloud-based models to increase efficiency, productivity, and revenue. Gartner states global cloud computing spending will likely touch $679 billion.  Both public and private clouds are in demand. Additionally, businesses opt for a multi-cloud strategy to streamline their operations and enhance overall performance. Statistics show that over 70% of enterprises will use industry cloud platforms by 2027. While almost 80% of businesses use multiple public clouds, 60% use a minimum of one private cloud.  So, what are the recent trends in cloud computing? How is cloud transformation influencing the global markets? What do we need to know about cloud digital transformation in an enterprise?  Read on to know more! What is Cloud Transformation? Cloud transformation is the process of migrating or transferring the business systems, IT infrastructure, data, processes, etc., from on-premises to a remote cloud platform. It focuses on scalability, flexibility, and agility to ensure that the technologies used align with the business requirements and the latest market trends. For example, outdated legacy systems are modernized or replaced by lighter cloud-based applications for better usability and faster results.  What is the Market Trend for Cloud Computing? There are many trends in the cloud computing market, which directly and indirectly influence how businesses use the latest technologies to achieve their goals. According to Mordor Intelligence, the cloud computing market size is expected to be $0.68 trillion. It is predicted to grow at a CAGR (compound annual growth rate) of 16.40% to touch $1.44 trillion by 2029.  21 Biggest Cloud Transformation Trends in 2025 1. Serverless Computing  Serverless computing is a model where developers can build and deploy application code without managing backend servers. It is also called function as a service (FaaS) where cloud service providers maintain the servers. The term serverless doesn’t imply the lack of a server but indicates that the server is not hosted on-premises in an organization. This reduces the cost of building and upgrading the IT infrastructure in the enterprise and promotes greater scalability. It helps businesses be ready to tackle future developments quickly and efficiently.  2. Better Artificial Intelligence and Machine Learning  While AI and ML technologies are already being adopted by many businesses, the trend will continue in 2025 and beyond. Tech giants like Google, IBM, etc., are coming up with new products and services that will boost productivity in organizations and empower employees to use advanced tools. AI and ML are a part of cloud transformation and help in streamlining various activities in different departments, verticals, and industries. Be it procurement or customer service, AI applications can be used for analytics, automation, and more.  3. Edge Computing  Edge computing is another trend in cloud transformation services. It aims to reduce latency and improve data processing speed. In this method, data storage and computing tools are brought closer to the data source, or all applications are hosted on the same server. This allows real-time analytics and report generation as applications run faster. For example, manufacturers can benefit from edge computing by setting up analytical tools near IoT (Internet of Things) devices or in the same network.  4. Multi and Hybrid Cloud  Cloud transformation doesn’t mean a business has to move all its systems onto a single cloud. In fact, many organizations prefer multi-cloud architecture to save costs and increase efficiency. By using individual apps hosted on the respective vendor cloud servers, businesses can reduce the costs needed to build everything from scratch. Furthermore, the responsibility for data security and privacy lies with the vendor. Large enterprises use a combination of public and private clouds to spread the workflows on different platforms according to their priorities and security requirements.  5. Sustainability and Green Computing  Sustainability is a hot topic in many industries. How can one make the IT industry also sustainable? That’s where green computing comes into the picture. Sustainable technologies align with environmental protection goals and can help businesses reduce their consumption of natural resources without affecting their daily activities. The aim is to reduce carbon footprint and create a circular network for IT-based energy consumption.  6. Industry Cloud Platforms Industry cloud platforms (ICPs) combine the capabilities of software, platform, and infrastructure as a service to provide customized solutions based the business requirements. This creates greater flexibility for organizations to handle any range of workloads without worrying about system crashes or unexpected downtime. Oracle Fusion Cloud and SAP DMC SAP Leonardo are some examples of industry cloud platforms. Businesses from each industry can get services that are tailored to their sector as well as the specific requirements.  7. Disaster Recovery  When creating a strategy for digital transformation, businesses should include disaster recovery and data backup on the list. With many organizations migrating their systems to cloud platforms, it is vital to understand the importance of securing the data and applications from cyberattacks or natural disasters. Fortunately, the leading cloud service providers offer disaster recovery tools to quickly retrieve lost/ corrupted business data and apps to restart the processes without wasting too much time. Instead of worrying about data loss, the organization can revert to the latest previous update and take it from there.  8. Internet of Things (IoT) IoT or the Internet of Things are devices like sensors, connectors, etc., that extract data from the source and exchange it with other devices in the network. The data collected by IoT devices is sent to analytical tools to derive actionable insights. IoT has an important role in industries like manufacturing, mining, oil and gas, chemical, pharma, etc. IoT is a combination of different tools and technologies that collect varied data like temperature, movement, equipment motion, etc.  9. Security and Resilience  While effective cloud transformation processes are one aspect

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Parsing Dynamic JSON Data in Power Query: A Quick Coding Guide

Learn how to efficiently convert any JSON data into a fully expanded table format using Power Query, reducing the need for custom code and streamlining your data processing. Introduction: Understanding JSON Data and Power Query  JSON (JavaScript Object Notation) is a lightweight data-interchange format that is easy for humans to read and write and easy for machines to parse and generate. It’s widely used in web services and APIs to exchange data between clients and servers. JSON’s structure typically includes nested arrays and objects, making it flexible for various types of data but also challenging to work with when it comes to data transformation and analysis.  Power Query is a data connection technology that enables you to discover, connect, combine, and refine data across a wide variety of sources. It is integrated into Microsoft products like Excel and Power BI, providing users with a powerful tool to transform and prepare data for analysis. Power Query’s ability to automate data transformation tasks and handle large datasets makes it an essential tool for business intelligence professionals.  The Challenge with JSON Data  JSON (JavaScript Object Notation) is a common data format, especially in business contexts where data is exchanged between systems. While JSON’s nested structure is useful for organizing data, it can be challenging to work with tools like Power BI, where a flat table format is often required for analysis. Traditionally, handling varied JSON structures involves writing custom code for each case, which can be time-consuming and difficult to maintain. To address this, we developed a Power Query solution that dynamically converts any JSON data into a fully expanded table format. This blog explains how the solution works, provides the code, and highlights the key logic behind it.  The Problem: Handling Varied JSON Structures  JSON files often contain nested records and lists, making it difficult to transform them into a usable table format. Manually writing different code for each variation of JSON data can be tedious and error-prone, especially when dealing with data from multiple sources or systems.  Our goal was to create a solution that could handle any JSON structure, automatically expanding it into a flat table without the need for constant code adjustments.  The Solution: Dynamic JSON Parsing with Power Query  We created a two-part Power Query script—JsonParser and ColumnExpander—that dynamically parses and expands JSON data into a table. Here’s a brief overview of how each script works:  JsonParser: Loading and Parsing JSON Data  The JsonParser script is responsible for loading the JSON data from a SharePoint site, parsing it, and preparing it for expansion.  let JsonParser = (FileNameWithoutExtension as text) => let JsonFileName = FileNameWithoutExtension & “.json”, SharePointFilesList = SharePoint.Files(“https://YourSharepointSiteURL/”, [ApiVersion = 15]), FileContent = SharePointFilesList{[Name=JsonFileName, #”Folder Path”=”https://YourSharepointFolderURL”]}[Content], JsonParsedData = Json.Document(FileContent, 1252), DataAsTable = if JsonParsedData is record then Record.ToTable(JsonParsedData) else if JsonParsedData is list then Table.FromList(JsonParsedData, Splitter.SplitByNothing(), null, null, ExtraValues.Error) else null, ExpandedData = if DataAsTable <> null then ColumnExpander(DataAsTable, 0) else null in ExpandedData in JsonParser Key Points: ColumnExpander: Expanding All Columns  The ColumnExpander script is designed to recursively expand any nested lists or records in the table, ensuring that the JSON data is fully flattened into a table format.  let   ColumnExpander = (TableToExpand as table, ColumnToExpand as number) =>     let       CurrentColumnIndex = ColumnToExpand,       CurrentColumnName = Table.ColumnNames(TableToExpand){CurrentColumnIndex},       CurrentColumnContents = Table.Column(TableToExpand, CurrentColumnName),       HasRecords = List.Contains(List.Transform(CurrentColumnContents, each _ is record), true),       HasLists = List.Contains(List.Transform(CurrentColumnContents, each _ is list), true),       CanExpandColumn = HasRecords or HasLists,       IntermediateTable =         if CanExpandColumn then           if HasRecords then             let               RecordFieldsToExpand = List.Distinct(                 List.Combine(                   List.Transform(                     CurrentColumnContents,                     each if _ is record then Record.FieldNames(_) else {}                   )                 )               ),               NewExpandedColumnNames = List.Transform(                 RecordFieldsToExpand,                 each CurrentColumnName & “.” & _               )             in               Table.ExpandRecordColumn(                 TableToExpand,                 CurrentColumnName,                 RecordFieldsToExpand,                 NewExpandedColumnNames               )           else if HasLists then             Table.ExpandListColumn(TableToExpand, CurrentColumnName)           else             null         else           TableToExpand,       FullyExpandedTable =         if CanExpandColumn then           ColumnExpander(IntermediateTable, CurrentColumnIndex)         else if CurrentColumnIndex = (Table.ColumnCount(IntermediateTable) – 1) then           IntermediateTable         else           ColumnExpander(IntermediateTable, CurrentColumnIndex + 1)     in       FullyExpandedTable in   ColumnExpander Key Points: Why This Solution Matters  This Power Query solution simplifies the process of working with JSON data. Instead of writing new code for each variation in your data, you can use these scripts to automatically flatten any JSON structure into a table. This saves time, reduces errors, and streamlines your data processing workflow.  Conclusion  Transforming JSON data into a usable format doesn’t have to be complicated. With the JsonParser and ColumnExpander scripts, you can automate the process of expanding JSON data into a table, allowing you to focus on what really matters—analyzing and using your data.  If your business is dealing with complex JSON data and needs a reliable, scalable solution, contact us today to learn how we can help you streamline your data processing workflows.  FAQs Q1: What exactly is this solution designed to do?  The solution suggested above is designed to dynamically transform JSON data of varying structures into a flat, table format using Power Query. It automates the expansion of nested records and lists within the JSON, eliminating the need for manual adjustments or custom coding for each new JSON structure.  Q2: How does this solution differ from traditional JSON processing methods  Traditional JSON processing often involves writing specific code for each unique JSON structure, which can be time-consuming and prone to errors. This solution, however, is flexible and dynamic, allowing it to handle any JSON structure automatically. It simplifies the process by recursively expanding all nested elements, making the data ready for analysis without the need for manual intervention.  Q3: Can this solution handle any type of JSON data?  Yes, it can dynamically expand any JSON data, whether it contains nested records, lists, or a mix of both.  Q4: Is this solution scalable for large datasets?  Absolutely. Power Query is optimized for handling large datasets efficiently, although performance may vary depending on the complexity of the JSON.  Q5: How does this compare to other JSON parsing methods in Power BI?  Most methods require manual adjustments for different JSON structures. This solution automates that process, making it more efficient and reducing the risk of errors.  Q6: Can these scripts be customized for

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21 Latest AI Chatbot Solutions for B2B and B2C Enterprises

AI Chatbot solutions are intent based computer programs that specifically uses artificial intelligence to bring a conversational approach to B2B and B2C consumers. In this article, let’s know the latest AI chatbot solutions and how it will enhance your product development and offer personalization to your customers.   The development of AI has given birth to large language models and Generative AI. Both these show that the global LLM market is expected to grow at a CAGR of 79.80% and will touch $2598 million by 2030. The use of AI is not limited to one specific industry; however, it’s increasing to release quality products into the market. The development of chatbot solutions driven by LLM can process data to deliver responses and perform other tasks. By processing data and interpreting insights, LLMs help you discover dangers early on and devise solutions for problems. Innovation and originality in product development are further aided by the use of language models in AI.  AI chatbot development solutions play a significant role in the development of AI products and recommendation engines. LLM and generative AI chatbots can offer valuable insights and intelligence to streamline various aspects of the product development process. Before building actual prototypes, AI-powered systems may simulate a variety of scenarios, identify any design problems, and enhance product performance. This guarantees that the finished product meets or exceeds client expectations by cutting down on the time and expense of multiple iterations. In this blog, we will understand how AI chatbot solutions can transform your day-to-day business processes. We will also understand the latest 21 AI chatbot solutions you can use as a part of the AI product development process.  Latest AI Chatbot Solutions To Follow  AI-powered chatbot solutions that utilize cutting-edge AI technologies have the potential to revolutionize the product creation process. Here’s how the listed chatbots can help at different phases of the product development lifecycle: 1. ChatGPT Based on consumer demands and current trends, ChatGPT can help with brainstorming sessions by producing original ideas and suggestions for new features or enhancements to existing products. ChatGPT helps in analyzing consumer reviews and may gather useful information from a vast amount of consumer evaluations and feedback to improve the functionality and design of products. Using AI chatbot solutions product innovation can result in resolving several operational challenges in business. Thus, ensuring automotive processing and increasing efficiency.  2. Google Dialogflow Dialogflow may oversee user interactions to gather thorough input on how the product is used and performed. You can utilize this data to find areas that need improvement. It will also help in performing market research and collecting data from conversational surveys to validate product ideas and comprehend user preferences. With Google Dialogflow AI chatbot solutions, gathering consumer feedback to facilitate testing becomes easy. This tool can integrate a conversational user interface face and interactive voice response systems. Dialogflow chatbots can spot new trends and changes in the industry by keeping an eye on social media and news sources. 3. IBM Watson Assistant IBM Watson Assistant is a platform that leverages natural language understanding and machine learning to gather and analyze extensive customer feedback. This tool can allow product teams to make data-driven decisions and tailor their offerings to meet market demands. It can offer personalized recommendations to fine-tune product features to enhance customer satisfaction. Moreover, Watson Assistant streamlines project management eliminates repetitive processes, and promotes real-time development team engagement through its seamless interface. Watson Assistant helps companies stay ahead of the competition by spotting trends, keeping an eye on rival products, and providing ongoing learning and development.  4. Microsoft Bot Framework Microsoft Bot Framework is an AI chatbot development solution by Microsoft that covers a wide range of topics like data collection, model training, and model deployment. This bot framework is an open-source visual authoring canvas for developers and other team members to design and build conversational experiences for users with language understanding. With the help of this framework, chatbots can interact with users through a variety of channels, gathering varied input and information from different touchpoints to guide product development. Chatbots based on this framework can validate new features and evaluate their effect on user satisfaction by interacting with Azure AI services. 5. Amazon Lex Amazon Lex can be used to build conversational interfaces for applications using voice and text. It enables natural language chatbots into your new and existing applications. This AI product development tool offers deep functionality and automatic speech recognition to build a highly engaging user experience, create new categories of products, and facilitate conversational interactions. Before a product is released, Amazon Lex may oversee user testing and beta programs, gathering and evaluating user input to make sure it is intuitive and up to par. Because of its integration capabilities with other AWS services, the development process is streamlined by controlling workflows, automating repetitive operations, and enabling real-time team collaboration. This ultimately leads to improved customer satisfaction and product quality.  6. Rasa  Rasa is a generative AI service that helps in developing assistants. Rasa helps businesses create chatbots that can interact with users in a more human-like and intuitive manner. Through conversational engagement, this chatbot may collect specific and in-depth feedback from customers, offering valuable insights into user preferences, problems, and desired features. Product teams can use this input to inform decisions, improve current products, and create new features that appeal to their target market. Through its ability to streamline communication, automate repetitive operations, and offer profound insights into user behavior, Rasa enables product development teams to create and produce superior solutions that surpass customer expectations and fulfill market demands. 7. Zendesk Answer Bot  Zendesk Answer Bot is an AI chatbot solution that enhances product development by automating customer interactions and providing valuable insights. This answer bot leverages natural language processing to effectively handle customer inquiries by delivering relevant and accurate responses from the database. Zendesk Answer Bot collects and evaluates user input when developing new products. It is capable of recognizing frequently asked queries, requested features, and

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Digital Transformation for Banks: How Can Banks Thrive in a Digital World?

Digitization gives banks a competitive edge by promoting innovation. Here, we’ll discuss the importance of investing in digital transformation for banks and how partnering with consulting companies can help the industry embrace the digital-first model.  The banking industry is embracing new technology and keeping up with the technological changes in the world. We have come a long way from visiting the bank for every transaction to managing our accounts online 24*7. Banks are now adopting digital transformation strategies to further enhance their financial products and relevant services.  According to a study report by CU Insight, the percentage of active digital banking users had increased to 77% in 2024. Mobile deposits increased from 52% in 2023 to 54% in 2024. 42% of financial institutions are already using machine learning algorithms to streamline operations.  Digital transformation for banks empowers the institutions to gain a competitive edge and thrive in today’s digital world. It helps banks strengthen their position in the market by increasing profits and improving customer experience. For this, banks partner with digital transformation consulting companies and implement a long-term plan to achieve their objectives.  Let’s read more about the importance of digitalization and digital transformation in the banking sector. Why are Banks Moving to Digital? Banks and financial institutions deal with a lot of paperwork and complex procedures. This is time-consuming, cost-intensive, and stressful. As the internet became more accessible, banks slowly upgraded their services to offer digital alternatives for customers. Now, with technology advancing quickly, the industry has no option but to continuously upgrade and cater to customer demands. Digital transformation in banking and financial services is not a choice any longer but a necessity. The increase in private banks and market competition has also played a role.  Moreover, digitization decreases the workload while reducing the risk of human error. There is a digital trail for transactions, making it easy to maintain a proper record. Automation has helped banks and customers make payments online from any place and at any time. The interconnectivity between bank branches and banks has increased. With such benefits, it is easy to see why digital transformation in retail banking has become popular around the globe. With countries like India promoting cashless transactions by encouraging UPI and online payments, we can say that digital banking is here to stay.  How Does Digital Technology Affect Banks? Digital technology offers many benefits for banks. While the institutions should be aware of the challenges, there’s no denying the importance of adopting new and digital technology to revamp banking services. Customers no longer have to visit the bank branch for minor transactions. They can send and deposit money online. They can check their account balance online. Net banking and mobile banking services have increased efficiency and customer satisfaction.  Digital transformation for banks has further enhanced the results. Now, banks can automate repetitive internal tasks, increase operational efficiency, use real-time analytics to make better decisions, improve data security, detect and prevent fraud, and deliver greater satisfaction to customers. It allows banks to offer personalized services to customers based on their preferences and transaction patterns.  What is Digital Transformation in a Bank? The digital transformation definition states that it is a strategic and continuous process of adopting and implementing digital technologies in an organization to streamline operations, optimize resources, create and modify products/ services, and improve customer experience. This is done by converting the processes into digital formats. Digital transformation and changes to banking services also include redefining the cultural aspects of the establishment. Adopting digital technology requires changes in the work culture. Banks need to bridge the talent gap and help existing employees navigate the changes without feeling stressed.  What is the digital transformation of the bank branch? Generally speaking, the digital transformation of a bank branch is where the institution converts analog data to digital data and invests in new tools and technologies like artificial intelligence, machine learning, big data analytics, data visualization, data warehousing, etc. This requires a compressive cloud–based digital transformation strategy and support from expert professionals. By partnering with reliable service providers, banks can overcome the challenges of digital transformation and amplify the benefits. Long-term support from digital transformation companies also ensures that banks regularly upgrade their technologies and minimize the risk of glitches or downtime.  Benefits of Digital Transformation in Banking  Digital transformation for banks is much more than enabling banks to offer online banking services to their customers. It offers various benefits such as the following:  What are the Four Pillars of Digital Transformation in Banking? The banking digital transformation framework is built on the following four pillars:  What is Digitalization in Banking? Digitalization in banking is the transformation of the IT infrastructure in banks to adopt modern technologies. A report by Markets and Markets shows that the global digital banking platform market is expected to reach $13.9 billion by 2026. Digitalization allows banks to build and implement custom applications to overcome roadblocks and streamline workflows across the institution. The front-end and back-end are given equal importance. Website and mobile app development, digital marketing strategy for banks, phone banking services, automating data, data analytical dashboards for decision-making, shortening the application processing cycle, developing customer-friendly financial products, AI chatbots for 24*7*365 support services, etc., are some examples. What is Digital Strategy in Banking? Digital acquisition strategy for banks refers to the blueprint describing the steps the bank should take to acquire digital technologies in its day-to-day operations. In today’s world, banks are encouraged to follow a digital-first approach where they prioritize digitalization and new technologies.  The success of digital transformation depends on the strategy and its implementation. That’s why many banks are hiring digital transformation consultants to handle the process from start to finish.  The end-to-end digital transformation strategy includes the following:  Digital Transformation Challenges Faced by Banks Digital transformation for banks is not without a few barriers or roadblocks. Banks should have a proper plan to tackle these issues to avoid facing losses.  Lack of Clarity in Estimating Costs  When calculating the costs, make

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How to Scale Your Startup With Managed Data Analytics?

Data analytics is the process of collecting, storing, and analyzing large datasets to derive actionable insights in real-time. Here, we’ll discuss the role of managed data analytics in scaling a startup and the benefits of adopting the data-driven model for decision-making. Startups usually begin on a small scale and expand over the years. However, scaling a startup is easier said than done. As per a study by the Kauffman Foundation, just one startup in every ten scales is successful. That’s when startups are worth $1215 billion in 2024, and the value of unicorns around the globe is estimated to be $4.3 trillion.  So how do you scale your startup and ensure success in 2024 and beyond?  Managed data analytics and artificial intelligence are the answers. Startups need to be proactive and take advantage of the data and technologies available in the market to establish themselves. Instead of following conventions and orthodox business models, startups should adopt data-driven models and advanced tools (cloud solutions, AI, ML, etc.) to reduce the risk of failure. Fortunately, plenty of third-party companies offer onshore, near-shore, and offshore managed analytics services tailored to suit the business requirements.  In this blog, we’ll read more about how to successfully scale a startup by investing in data analytics and the benefits of using managed analytics in a new business. How do You Scale up Your Startup?  Scaling a business is the process of growing or expanding the operations, products and services, market share, customer base, and returns. Startups scale to invite more customers which brings higher revenue and creates a brand image in the market. However, scalability can be limited to one or specific avenues as well. Not every startup scales all aspects together.  Typically, you can scale a startup in any of the following ways:  What is an example of a Scalable Startup? Is Managed Data Analytics Involved? Facebook, Twitter (now X), and Amazon are great examples of a scalable startup. These started as small companies run by the entrepreneur and a couple of friends or team members. Over the years, Amazon has become the number one international marketplace and Facebook is one of the tech giants. They heavily invested in business analytics (gradually) to make decisions backed by data and insights. This allowed them to quickly adapt to the changing market conditions and gain a competitive edge. How do Startups Use Managed Data Analytics? Startups cannot underestimate the importance of data analytics in modern times. From streamlining internal processes to increasing customer satisfaction, analytics can be helpful in several ways. It converts raw data from multiple sources into actionable insights that employees can access to complete daily tasks more effectively.  Understand Target Markets  Startups don’t have the luxury of taking major risks or investing all the money into a project without basic research. Nine out of ten startups fail and shut shop in less than a decade. This can be due to lack of funds, incorrect investments, wrong decisions, etc. Understanding the target market conditions can reduce the risk of losses and keep the business afloat. For this, you can rely on data analytics to process the datasets related to the market and derive meaningful insights. Third-party companies offer managed analytics solutions and embedded analytics to provide real-time insights whenever you need them.  Analyze Customer Behavior  Customer feedback is vital for every business, and startups need it more than ever. However, you cannot afford to spend your time and resources on manually analyzing this feedback. Data analytics simplifies the process by using powerful tools and sharing the reports through data visualization dashboards. Platforms like Power BI, Tableau, etc., are popular data analytics tools that can be integrated with various input and output systems to provide insights 24*7.  Evaluate Competitors  How else do startups use data analytics to grow their business? Managed data analytics is not limited to analyzing the internal aspects of a business. You can use public data to determine who your competitors are and how they are faring in the market. This helps in identifying weak areas in your startup and strengthening them to survive the competition. Similarly, you can track the performance of your competitors and identify growth patterns to plan your strategies accordingly.  Improve Products and Services  Startups face severe competition from existing and new businesses. This means you have to continuously tweak your products and services to increase sales and bring more customers. Data analytics helps by highlighting the purchase patterns and preferences for your offerings and in the market. It provides information about what customers like and how you can improve your products and services to generate more sales or get the desired number of subscriptions.  Streamline Internal Operations  As a startup, you don’t have access to unlimited funds. You need to make some strict decisions about where to invest, what to prioritize, etc. In such instances, managed data analytics can help by identifying processes or steps that consume excess resources but are not necessary for the business. You can shorten the cycles, automate recurring tasks, and trim areas without compromising quality. It also helps in negotiating better deals with suppliers, storing your inventory carefully to reduce wastage, increasing or decreasing production/ procurement to align with the market demand, etc.  Increase Conversion Rate  Marketing is another area where data management services and analytics can help your startup. A new business has to invest in offline and online marketing campaigns to reach the target audience. Generating leads is one aspect, and converting them into sales is another. Startups tend to have a hard time converting leads to sales. Data analytics can be used to create a marketing strategy that suits customer preferences. Identifying the right kind of audience and sending the right message to the right customer at the right time through the right channel is possible when you use data analytics.  Identify More Avenues for Revenue  Revenue cycle analytics gives startups in the healthcare and finance industries a clear idea to streamline their revenue generation avenues. It tracks every step

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