Page 5 – DataToBiz

Yashica Chopra
December 18, 2024
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Your 10 Step Guide to Data Domination in 2025

Data domination allows businesses to make informed and data-driven decisions using real-time actionable insights. Here, we’ll discuss the guide to data domination through tailored data engineering services for your business. Data domination is the process of streamlining and effectively managing datasets to benefit from the data-driven model and make proactive decisions. It is a blueprint to implement data engineering and management solutions in your enterprise. So does it mean data engineering necessary is in 2025? Absolutely! Statistics show that the global big data and data engineering market will be $75.55 billion in 2024 and expected to reach $169.9 billion by 2029 at a CAGR (compound annual growth rate) of 17.6%. It is evident data engineering services are not only necessary for 2025 but will continue to play a prominent role even afterward. Of course, data domination is easier said than done. You should consider many factors like data collection methods, data ingestion, safe and secure data storage, long-term maintenance, troubleshooting, etc. Not addressing these concerns can lead to failed data management systems. That would be counterproductive, isn’t it? Luckily, you can overcome these challenges and more by partnering with a reliable data engineering company. Hire experts from the field to mitigate risks and increase your success rate. Let’s check out the detailed guide to data domination in 2025. Before that, we’ll find out how to overcome the challenges in data engineering. Challenges for Data Domination and How to Overcome Them As per Gartner, poor data quality leads to a loss of $15 million annually for businesses around the world. Avoiding this and many other pitfalls is easy when you make informed decisions. By overcoming these challenges, you will be several steps closer to data domination and gain a competitive edge. Data Ingestion Data ingestion refers to feeding data from multiple sources into your systems. It is one of the initial steps of data engineering solutions. The data ingested is then cleaned, processed, and analyzed to derive insights. A few challenges you might face are as follows: These issues can be sorted by in-depth planning. Instead of immediately connecting the data sources to your systems, take time to identify the right sources and set up data validation and cleaning processes (ETL and ELT). Automate the process to save time and reduce the risk of human error. Determine your budget and long-term goals when deciding the data ingestion method. Migrate to cloud platforms for better infrastructure support. Data Integration Data integration depends on how well the various software solutions, applications, and tools used in your enterprise are connected to each other. Naturally, data will be in different formats and styles depending on the source. A few more challenges are listed below: For seamless data integration, you should first create a data flow blueprint. Then, identify software solutions that are not compatible with others (legacy systems) and modernize or replace them. Since you have to integrate different data types (structured, unstructured, and semi-structured), you should invest in data transformation tools. Azure data engineering services cover all these and more! Data Storage The biggest concern about data storage is scalability. With so much data being collected in real time, where will you store it? Moreover, how much can your data storage centers handle the load? What to do with old data? How hard will it be to retrieve data from the storage centers? Here are more challenges to consider: Choosing the wrong data storage model can adversely affect the entire data engineering pipeline. Migrating to cloud servers is an effective way to overcome these roadblocks. For example, Azure, AWS, or Google Cloud platforms offer flexible, scalable, and agile data warehousing solutions. You can set up a customized central data warehouse that can be upgraded whenever necessary. A data warehouse is capable of handling large datasets and can quickly respond to queries. Data Processing Traditional data processing tools cannot handle diverse data. They also cannot process large datasets quickly. Processing data from silos can lead to data duplication and reduce the accuracy of the results. There are more data processing concerns, such as: Modern problems require modern solutions. Instead of struggling with traditional tools, switch over to advanced technologies and AI-powered data processing tools. Similarly, data silos have to be replaced with a central data repository like a data warehouse or a data lake. Partnering with AWS data engineering companies will help you identify the right tools and technologies to process data in real time and share the insights with employees through customized data visualization dashboards. Data Security and Privacy Data brings more challenges with it. After all, you are using data that includes confidential information about your customers, target audiences, competitors, and others. How to ensure this data is safe from hackers? How to avoid lawsuits from others for using their data for your insights? Common data security concerns are: Data security should be included as a part of data warehousing services. Data encryption, data backup, disaster recovery management, authorized access to stakeholders, security surveillance, security patch management, and employee training (to create awareness about cyber threats), etc., are some ways to overcome these challenges. The service provider will also create a detailed data governance guide to provide the framework for regulatory compliance. 10-Step Guide to Data Domination in 2025 Step 1: Define Business Goals Always start at the beginning. Lay the foundations clearly and carefully. What do you want to achieve through data domination? How will your business improve through data engineering? What are your long-term objectives? Be detailed in defining the business goals so that your stakeholders and service providers understand the requirements. Step 2: Hiring a Data Engineering Company Data domination is not an easy task. It’s a multi-step and continuous process that requires expertise in different domains. While you can build a team from scratch by hiring data engineers, it is cost-effective and quick to hire data engineering or a data warehousing company. Make sure it offers end-to-end services and works remotely. Step 3: Create a Data Domination Strategy

Yashica Chopra
December 15, 2024
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AI as a Service – A Bold Move in 2025?

Artificial intelligence as a service (AIaaS) is a cloud-based solution for enterprises to invest in advanced technology. Here, we’ll discuss AIaaS, its role in today’s market, and how businesses achieve their goals by partnering with AI service providers. The adoption rate of artificial intelligence has increased multifold over the years. Many businesses, be they startups or established enterprises, are investing in AI in varied ways to gain a competitive edge and survive volatile market conditions. According to Grandview Research, the AI market is likely to experience an annual growth rate of 37.7% between 2023 and 2030. A report by Markets & Markets shows that the global AI market is predicted to reach $1.3 trillion by 2030. Fortunately for businesses, nonprofits, and government agencies, any organization can adopt AI technology on any scale. It can be a tiny part of your business process or be 100% integrated into all processes across the departments and verticals. Moreover, artificial intelligence services are diverse and customizable. Naturally, this led to a relatively new cloud-based AI offering called AI as a service (AIaaS). This is more convenient, budget-friendly, and effective compared to large-scale AI adoption and implementation. But what exactly is AIaaS? What does an AI services company do to offer artificial intelligence as a cloud service? Will it be a worthy choice for businesses in 2025? Let’s find out! What is the AI Model as a Service? AI as a service (AIaaS) is a new business model where service providers offer artificial intelligence-based solutions through a cloud platform. Instead of setting up the AI tools/ apps on-premises, the software is hosted on a remote cloud server and accessed by users whenever necessary. All technologies and tools under the umbrella term AI are available on the cloud. Be it machine learning algorithms, natural language processing (NLP) models, large language models (LLMs), generative AI apps, computer vision, advanced analytical tools, etc., can be accessed remotely to get near real-time and real-time results. In the AI as a service business model, you subscribe to use the required tools and software provided by the vendors. You pay only for what to use and not for all the other services offered. Additionally, the pay-as-you-go model allows startups and emerging businesses to save money on unwanted expenses. You can upgrade or downgrade the subscription plan as necessary. Furthermore, there’s no need to invest heavily in building the IT infrastructure in the office. Employees can use their personal devices and work from any location as long as they have been authorized to access the tools. What is the Purpose of AI as a service? As per Global Market Insights, the AI as a service market size is expected to grow at a CAGR (compound annual growth rate) of 28% between 2023 and 2032 and reach $75 billion by 2032. This growth rate can be attributed to the ease of using artificial intelligence as a cloud service. The main purpose of AIaaS is to eliminate the need for unwanted hardware and bring greater flexibility to the business’s IT infrastructure. AI as a service is diverse and can be classified into the following types. Whether you want to implement only one of the above or a combination (and all of them), the AI product development company will create a price plan accordingly and determine the subscription charges. That way, you pay for what you use while ensuring quality, scalability, agility, and personalization are not compromised. Of course, there can be a few concerns like data security, lock-in agreements, and transparency about the core AI systems used. However, these issues are a problem only if you choose a service provider at random. Many reliable companies that offer AI as a service address these concerns proactively. For example, DataToBiz is an ISO-certified AIaaS company that complies with global data regulations and has a transparent pricing model. The developers use existing cloud technologies or build new models based on clients’ requirements. With the right partner, you can vastly benefit from switching to the AIaaS business model. Why You Should Invest in AI as a service? What makes AI as a service a better alternative to implementing artificial intelligence in your business? Check out below. With AIaaS, an organization can quickly build, develop, and release products into the market. The production cycle can be shortened without affecting quality and performance. AI product development in today’s world results in low-code or no-code applications that can be built and customized in a fraction of the time usually required to develop a model from scratch. The drag-and-drop interfaces accelerate time to market and allow you to quickly launch new products before competitors. AI as a service is a long-term solution or an agreement with the service provider. As long as you pay for the subscription, you will get continuous improvements and upgrades offered by the company. In most enterprise price plans, you don’t have to pay extra for troubleshooting, upgrading, or maintenance services. The service provider offers these as a part of the package. Over the years, you gain more from the service and see positive growth in ROI. Advanced technology is not cheap, and not every business has the capacity to buy new tools and software as soon as they are released. What will you do with the existing apps? How many can you buy only to use for a limited period? However, with AI as a service, there’s no need to make huge purchases. You can use the latest tools without buying them outright. That makes it feasible for startups and small businesses to use technology just like large enterprises do. The stakes are lower as you can switch from one service provider to another or use a different platform if the current one doesn’t meet your expectations. As mentioned earlier, AI as a service offers more flexibility in choosing what features, tools, frameworks, and solutions to implement in a business. There’s no need to complicate the systems by trying to use every available option for its own sake.

Yashica Chopra
December 11, 2024
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Why do Growing Enterprises Need a Digital Transformation Consultant?

Digital transformation is a never-ending process of using advanced technology and data-driven models to make effective business decisions. Here, we’ll explore the need for hiring a digital transformation consultant to boost an enterprise’s growth and ensure consistent results. Whether you own a startup or belong to a multinational company, the organization uses a range of applications, systems, and tools to manage daily activities. In today’s world, businesses need to rely on technology to quickly achieve their goals. You cannot compete with digitally strong firms without investing in the latest technology. That’s where digital transformation helps. According to a survey by West Monroe, 61% of C-suite executives recognize digital transformation as a priority. A report by Valtech shows that 94% of large enterprises in the US and the UK have a digital transformation strategy in place to revamp their systems and processes. The same report says 58% of businesses aim to increase their spending on digital transformation compared to previous years. In such instances, it’s vital to understand what digital transformation is and how a digital transformation consultant can help you with the process from end to end. In this blog, we’ll focus on the role of a digital transformation consultant in a growing enterprise. What is Digital Transformation? Digital transformation is a continuous process and a business strategy to integrate various digital technologies into the business at different levels and verticals. It helps in evaluating the existing systems and modernizing them to create a digital-first approach to running the business. From procurement to production, operation management to customer service, and finance to marketing, every aspect of the business is streamlined using relevant digital technology. Modern-day concepts like personalization, agility, scalability, flexibility, etc., can be achieved by digitally transforming business processes. It is a comprehensive way forward to be proactive in competitive markets and increase brand visibility. Digital transformation, when rightly done, increases revenue for the organization and accelerates growth. Technologies like cloud computing, artificial intelligence, machine learning, advanced analytics, data science, big data, IoT (Internet of Things), edge computing, data visualization, business intelligence, etc., are a part of digital transformation. As an employee or a C-suite executive, you may ask – what is my role in digital transformation? Well, your role is varied and depends on how you want to digitally transform the enterprise. You need to work with an experienced digital transformation consultant to create the strategy, determine the budget, and initiate the process. What Does a Digital Transformation Consultant Do? According to Market Research Future, the digital transformation consulting market size was $205.87 billion in 2023 and is expected to reach $386.73 billion by 2032 at a CAGR (compound annual growth rate) of 7.40% between 2024 and 2032. With digital transformation explained in the previous section, let’s see what a digital transformation consultant does and how they can help your business. Digital transformation is different from digitization, which is a process of converting analog data into digital data. It has a wider scope and involves all parts of the business. A digital transformation consultant is a qualified and certified expert who guides business organizations in understanding, implementing, and managing the digital transformation journey. Consultants work as freelancers or can belong to a digital transformation services company. Their role is to help enterprises bridge the gap between technical knowledge and their long-term objectives, identify tools that align with the establishment’s needs, and create a holistic environment for employees to adopt the new technologies. However, this is a broader description of what a digital transformation consultant does. In reality, their work is much more complex and time-consuming. Their strategies are developed based on the requirements of each business and the unique challenges faced by them. From streamlining the processes in each department to automating repetitive tasks, setting up third-party integrations, and providing data-driven insights, the digital transformation consultant has to consider several aspects when assisting a business on its digital transformation journey. Why is Digital Transformation Important? Digital transformation consulting services are important in many ways in the modern-day scenario. From improving operational efficiency to enhancing customer experience, it helps growing enterprises harness the latest technologies to boost their business. It is not limited to a single industry and can be effective in any business. Despite being a tech-based long-term solution, its presence is useful in every sector and industry. The digital transformation strategy is prepared for the long term and empowers a business to continuously innovate and come up with better processes. Agile and DevOps practices are integrated with emerging technologies to make the applications more effective. Furthermore, it is helpful in future-proofing a business. The internal and external operations of an organization need to run in a smooth rhythm to provide the necessary products and services to customers (end-users). With digital transformation, you can optimize the operations using relevant tools, applications, and software. Automation is the process of using technology to perform the tasks previously handled by humans. This saves time, reduces the consumption of resources, and minimizes the risk of human error. It is a critical part of digital transformation and can increase the overall productivity of an enterprise. Customer satisfaction should be a priority for every business. The digital transformation approach is also designed with a focus on increasing customer satisfaction (attracting new customers and retaining existing ones). You can use customer analytics to understand their preferences and take steps to increase brand loyalty. Change is the only constant in today’s world. Enterprises cannot resist change if they want to survive market competition. Digital transformation empowers organizations to become more resilient in adverse conditions and be quick to adapt to new developments. Flexibility is one of the top benefits of digital transformation. AI and ML technologies, along with cloud solutions, can revamp the IT infrastructure in an enterprise to make the workflows more efficient and result-oriented. Digital transformation helps identify unwanted tasks and simplify the processes. This encourages resource optimization and makes it easier for employees to finish their tasks quickly. The digital strategy consultant’s

Yashica Chopra
December 10, 2024
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40 Top Rated Staff Augmentation Services Providers for 2025

Staff augmentation refers to an outsourcing model where a business temporarily hires an external team to work on its projects. Here, we’ll briefly discuss the top forty IT staff augmentation services providers to work with in 2025 to boost your business. Workplace and talent management strategies have changed over the years. Businesses have more options to experiment and find the most suitable model to balance cost with quality and get the desired output. Outsourcing has helped many enterprises reduce costs and save resources. This led to another model that comes under the broader outsourcing concept but gives organizations more control over the process. This model is staff augmentation. It is used to increase/ augment the capacity of your in-house talent by bringing external experts for a given duration. Be it repetitive work or specialized skills, staff augmentation can be used to hire any kind of talent quickly and cost-effectively. According to GlobalNewsWire, the IT staffing market in the US alone is expected to reach $39 billion by 2024. There is high demand for staff augmentation services around the globe. In fact, many SMBs and large enterprises are opting for different models, like team augmentation services or resource augmentation based on the diverse requirements of their projects. But, what is augmentation in the workplace? Simply put, staff augmentation refers to the practice of expanding an in-house team by hiring temporary employees from reputed companies. The external employees work with the existing teams as per the contract terms and deliver the promised results. Once the project ends, the team is dismantled and the external experts find other clients/ projects. Here, we’ll take a look at the leading IT staff augmentation services providers from different parts of the world. While some companies work with specific industries, a good number of them have a presence in many sectors and offer a plethora of other services. Top 40 Staff Augmentation Services Providers in 2025 DataToBiz DataToBiz offers on-demand IT staff augmentation services through different models, such as FTE (full-time equivalent), contract staffing, employee leasing/ PEO, and contingent staffing. With expertise in diverse domains, the company provides qualified and certified employees to handle complex projects for its clients. It is a certified partner of Microsoft (Gold), Google, and AWS. The award-winning company also has ISO certification and is SOC 2 compliant. Be it a startup or a multinational organization, any business can hire global talent through DataToBiz analytics staff augmentation services and build a team in 48 hours or less. Its cost-effective pricing model and scalable team solutions help businesses achieve their goals in a quick time. Coherent Solutions Coherent Solutions has a presence in ten global locations and is among the leading digital product engineering companies in the market. It offers dedicated teams to businesses with a focus on building strategic partnerships with them. The company’s team augmentation services are tailored to suit the changing needs of each client. It starts by understanding the client’s business model, vision, mission, and success criteria. Then, the company builds a team with skills and capabilities that align with the client’s requirements. Apart from data governance compliance, Coherent Solutions also takes care of maintenance services through continuous development. It prioritizes communication, accountability, and commitment. ValueCoders ValueCoders is a software development company offering staff augmentation and IT outsourcing services worldwide. It has full-cycle development experts to work on a project of any size and complexity. From UX/ UI design to security and extended support, the company provides customized teams that align with the specifications of each business. It works with startups and Fortune 500 firms, as well as growing organizations at different stages of success. The company uses proven methodologies and combines them with the domain knowledge of its employees to deliver the promised results to clients. ValueCoders has won several awards for providing reliable and measurable services. It is an ISO-certified company and a member of the AWS technology partner network. PixelCrayons PixelCrayons is a digital consulting and engineering firm offering end-to-end services to enterprises from various regions. The company’s offshore staff augmentation services are flexible, budget-friendly, and dependable. It provides IT teams on demand to help clients bridge the gap between existing talent and required talent. The experts are pre-vetted and optimized to work with the resources provided by the clients. From ideation to deployment, the company handles various tasks through its customized teams and delivers the projects within the schedule. PixelCrayons boasts of having a talent tool belonging to the top 1% of the IT industry. Businesses can choose from three staffing models – dedicated teams, project-based, and team augmentation. *instinctools *instinctools is a software development and consulting company offering innovative technological solutions to clients from various parts of the globe. Its staff augmentation services help clients close skill gaps, fast-track development, and reduce costs without compromising quality or results. The company knows that there’s no common solution and creates tailored teams based on the project requirements. It gives clients complete control over the augmented teams while providing the necessary support to help them achieve their goals. Information security, scalability (up and down), and quality are the three major focus areas for the company. Instincttools also has a flexible payment model where clients can pay only for working hours and save money. Vinova Vinova is a digital transformation and IT consulting company offering different types of staff augmentation services and collaboration models. Businesses can choose between scope-based models for fixed timelines and controlled budgets or opt for head count-based models like staff augmentation, dedicated teams, ODC, and time and material. The teams will have a project manager who oversees the entire process and maintains regular communication with the clients. Vinova is a partner of many leading vendors like AWS, Azure, Google, Salesforce, etc. The experts work with a plethora of technologies to provide innovative, advanced, and effective solutions to help businesses overcome their challenges and achieve long-term objectives. Miquido Miquido is a software development company offering flexible team augmentation services and ongoing support services with custom

Yashica Chopra
December 03, 2024
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Generative AI Services vs. Traditional AI – The Intelligent Choice?

Artificial intelligence comes in many types and forms. It has diverse uses in different industries and can support organizations to increase ROI and profits. Here, we’ll discuss traditional AI vs. generative AI services and how they help businesses in various ways. Artificial intelligence (AI) is the buzzword in today’s digital world. It is a part of our everyday lives in one way or another. With continuous research and development in the field, AI is becoming more powerful and useful on a large scale. For example, in the last couple of years, we went from using traditional AI to relying on generative AI. All types of AI are being discussed and implemented in different industries. Traditional and genAI are both used in businesses for various purposes. The global AI market was valued at $454.12 billion in 2023 and is expected to touch $2500 billion by 2032 at a CAGR (compound annual growth rate) of 19%. According to McKinsey, generative AI will add $2.6 trillion to $4.4 trillion worth of value to the global economy. But what exactly is traditional AI? How does generative AI differ from traditional AI? Should a business solely invest in generative AI services or should it stick to traditional AI? Which service is the right choice for a business? Let’s find out in this blog. What is Traditional AI? Traditional AI is a subset of the umbrella term artificial intelligence. It is also called narrow or weak AI and is predominantly used to perform tasks based on predefined parameters. The algorithms are trained to complete a set of actions for the given input. It can handle simple tasks efficiently and automate repetitive tasks as and when necessary. It also works well in domains where the rules don’t change often and follow a set pattern. For example, online gaming, industrial automation, workflow automation, data analytics, medical diagnosis, spam filters, recommendation engines, virtual assistants, etc., are some traditional AI use cases across industries. It helps with decision-making and problem-solving at various levels in the enterprise. Since the rules are explicit, traditional AI is more transparent and the algorithms are easier to understand. The AI applications offer domain-specific services and are fairly reliable. However, its limited learning capabilities and strict rules don’t offer a chance for the models to become more powerful. Many companies offer traditional AI consulting services for businesses to streamline their processes, shorten production cycles, and understand customer data. Existing models can be customized or new models can be developed from scratch to help organizations achieve their goals. Starting with traditional AI adoption usually helps as it allows employees to get used to new technology before dealing with advanced versions. sights. What is GenAI? Generative AI is a new take on artificial intelligence to provide more adaptive, flexible, and sophisticated algorithms. Unlike traditional AI, generative AI can create new content (text, images, audio, and videos) by analyzing large datasets to identify patterns. Instead of relying on strict rules or parameters, it learns by analyzing the input and datasets to provide a creative and unique result to the end user. For example, a generative AI application can process the input text and generate an image based on the prompt. It goes beyond what narrow AI can achieve and pushes the boundaries farther. Naturally, there are questions like – is GenAI related to LLM, or is ChatGPT a generative AI? The answer is yes to both questions. GenAI is a broader concept dealing with different types of models that generate content. LLM (large language model) is a specific form of generative AI and acts as a foundation model to run a wide range of NLP (natural language processing) tasks. ChatGPT by OpenAI is a form of generative AI that can converse with users like another human and provide a relevant answer/ result to their input. Generative AI also uses machine learning, deep learning, and neural networks to analyze the datasets and produce new content. While content creation, personalized recommendations, and virtual assistants are some uses of GenAI, it is not without some flaws. There is ambiguity in how the algorithms ‘create’ content and the use of public data for training the models can violate copyright and IP rights. Additionally, the generated content may not be 100% accurate or reliable as genAI is still in the development stage. Nevertheless, businesses can vastly benefit from generative AI services if they have a clear idea of what they want and how to use the applications to increase performance and reduce risk. Some services can be offered through traditional and generative AI. For example, AI chatbot solutions can be built on narrow AI and genAI models. What the chatbots can achieve depends on the type of model used. Naturally, generative AI-based chatbots are more conversational and can deliver better results, especially when trained on high-quality data. How is Generative AI Different from Other AI Approaches? Generative AI differs from other artificial intelligence approaches that focus on data analysis or making predictions. While both types analyze data and identify patterns, generative AI uses this to generate content and create something new, which other AI cannot do. Here, we’ll compare generative AI with other models to understand the difference. AI vs. Generative AI vs. Machine Learning We have already discussed the difference between AI (traditional) and generative AI. Machine learning is a subset of artificial intelligence that combines concepts like statistics and computer programming to identify hidden patterns and trends in diverse datasets. It uses data and algorithms to enable AI models to mimic how humans learn and can improve their accuracy through the feedback loop. Machine learning models are classified into three types – supervised, unsupervised, and reinforcement learning. The primary difference between generative AI and machine learning lies in how and when they are deployed. ML is a part of genAI applications and is used for prediction and optimization based on insights derived from data analysis. Generative AI analyzes data to create similar structures or samples exhibiting the required characteristics. Additionally, machine learning

Yashica Chopra
November 26, 2024
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AI’s A-List : 30 AI Companies to Know in 2025

Artificial intelligence companies offer diverse services to help businesses adopt new technologies across departments and verticals. Here, we’ll discuss the AI companies’ list of top thirty firms to watch in 2025. Artificial intelligence comes in many forms today. Be it conversational AI, responsible AI, or generative AI(LLM), each has a role in our society and business world. It’s no surprise that many businesses, ranging from startups to multinational giants, invest in AI at some level and use it as a part of their processes. While tech leaders develop their own AI models from scratch, other organizations prefer to hire service providers and use customized tools to achieve their goals and gain a competitive edge. Statistics show that the global AI market is expected to be valued at $214.63 billion in 2024 and is projected to reach $1,339.1 billion by 2030. As artificial intelligence revolutionizes different industries, the estimated annual growth rate is to be around 36.6% between 2023 and 2030, according to Grand View Research. As per McKinsey, AI adoption has increased by 72% in 2024. India has the highest adoption rate of 59%, followed by UAE (58%), and Singapore (53%). With such encouraging statistics, it’s evident that businesses are actively investing in AI technologies. They partner with reliable AI companies to find the best way forward for AI adoption. AI companies offer services in various ways, such as end-to-end, strategic consulting, managed services, AIaaS (AI as a Service), etc. In this blog, we’ll look at the top thirty AI companies to consider in 2025. Top 30 AI Companies for 2025 DataToBiz DataToBiz is a leading artificial intelligence and digital transformation company with ISO certification. As one of the top AI companies in India, it is a certified partner of Microsoft (Gold), AWS, and Google. The company offers diverse solutions like AI product development, computer vision, NLP (natural language processing), LLM (large language model), and machine learning. As an award-winning service provider, the company adheres to various global data security standards and provides tailored services for startups, Fortune 500 firms, SMBs, MSMEs, MNCs, and large enterprises from around the world. IBM IBM is a global AI and IT service provider offering adaptive solutions for mid to large-scale enterprises. The company builds safe and holistic AI models to encourage businesses to adopt the latest technologies in their establishments. Its services are customized, flexible, and scalable to suit the diverse needs of a growing and multinational organization. Additionally, it offers proprietary platforms like IBM Watsonx for businesses to streamline their processes and automate workflows. Google Google is a famous tech giant with a global presence. The company has many tools and apps for personal and business use. Apart from the suite of technologies in Google Cloud, it offers an array of AI and ML solutions for clients from different parts of the world. The company caters to startups as well as large enterprises and has something for everyone. Gemini is Google’s generative AI offering and has many models that can be customized to help businesses overcome various challenges. Microsoft Microsoft is another technology giant with an international market base. Its cloud solution, Azure, is among the top three platforms used globally. The company has varied services to suit the dynamic requirements of startups, SMBs, and large organizations. It assists businesses in confidently adopting AI solutions in all verticals and enables digital transformation. Be it Teams, Dynamic 365, Power Platform, or GitHub, businesses can customize and integrate these solutions to achieve their objectives. NVIDIA NVIDIA is a popular company known for developing a wide range of computer components. However, it is also an active service provider offering ready-to-use AI platforms in enterprises. The company builds powerful artificial intelligence models for developers, executives, and general IT services. NVIDIA NIM can be used to instantly deploy generative AI and scale the capabilities with ease. The company ensures data security and provides many cybersecurity solutions. It also provides conversational AI and vision AI services. Amazon Amazon is a global cloud platform (AWS) offering a diverse suite of technologies, tools, applications, and frameworks for SMBs and large enterprises. It works with varied clients and provides direct and indirect services. Like Google and Microsoft, Amazon also offers certification for third-party developers to provide customized AI development and managed services to businesses. The company builds its AI and ML models from scratch to automate workflows, streamline database management, and simplify complex tasks. DataRobot DataRobot is a data science and artificial intelligence company that helps businesses accelerate their AI adoption journey from ideation to implementation. It has many AI platforms that can be tailored to meet the changing requirements of organizations from different industries. The company follows a value-driven approach and sets high standards for businesses to understand and use AI technologies for numerous purposes. BEACON, LATTITUD, Women@DR, Pridebots, ACTNow, etc., are some efficient AI tools developed by the company. Machina Labs Machina Labs is an AI and robotics company offering a reliable and customizable platform to encourage agile manufacturing on a large scale. The Robotic Craftsman platform has been developed by the company based on advanced AI models and closed-loop controls. The solutions can be scaled, making the company a worthy partner for large establishments and government agencies. The company’s offerings reduce time and cost by creating prototypes quickly. It provides innovation, design, and engineering services as well. PwC PwC is a global consulting company offering a range of services to clients from around the world. It provides tailored solutions using responsible AI, generative AI, and other IT business services. The company’s cloud-powered services help organizations build secure, flexible, and scalable platforms/ applications to streamline business processes and enhance output. It provides strategy development and consulting services for businesses to make the right decisions using data-driven models. General Motors General Motors is an automobile manufacturing company with decades of experience in the industry. The company has extended its presence in the AI field by developing different solutions to enhance the safety of using vehicles. It calls itself the

Yashica Chopra
November 19, 2024
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Top 20 Data Analytics Companies Shaping 2025

Data analytics is vital for organizations from any industry to unlock the power of their data and convert it into actionable insights. Here, we’ll discuss the top twenty data analytics companies worldwide and know their role in helping businesses make data-driven decisions. In a world where a massive amount of data is generated daily, it would be a colossal waste to not use this data to derive meaningful insights, patterns, and trends. Whether you want to understand what customers like or how the market conditions will change over a given period, you can use data analytics to get the necessary insights. Data analytics is the process of collecting, cleaning, storing, and analyzing datasets from various sources to derive insights that help in making better business decisions. Businesses need to invest in data engineering and data analytics to optimize their processes, improve efficiency, and enhance customer experience. You can build your data analytics model from scratch or partner with a service provider to get managed data analytics services. Statistics show that the global data management and analytics market is expected to touch $513.3 billion by 2030 at a CAGR (compound annual growth rate) of 16%. Another report indicates that the big data analytics market will be $348.21 billion in 2024 and is likely to reach $924.39 by 2032 at a CAGR of 13%. The estimated growth rates are proof of increasing investment in data analytics. Naturally, there is a high demand for data analytics companies in India and other countries around the globe. In this blog, let’s take a look at the top twenty data analytics companies offering consulting services and managed analytical solutions for businesses from different industries. Top Data Analytics Consulting Firms Shaping 2025 DataToBiz DataToBiz is among the leading data analytics companies in India offering an array of services for digital transformation, business intelligence, data engineering, cloud computing, etc., using AI and ML technologies. The award-winning company provides tailored services for predictive analytics, descriptive analytics, customer analytics, supply chain analytics, financial analytics, and many others necessary for businesses to make data-driven decisions in real-time. With clients from numerous industries, DataToBiz has expertise in working with startups, SMBs, MNCs, MSMEs, and large enterprises. It provides data analytics consulting services, implementation solutions, data analytics as a service, and data analytics support and evaluation to help businesses strategize, build, deploy, integrate, and maintain the analytical models in their establishments. Get customized end-to-end data engineering and data analytics services by partnering with the company. Glassdoor Rating: 4.8 Stars Accenture Accenture is a global analytics services company offering extensive data services for large enterprises from different parts of the world. It uses artificial intelligence to build data analytics and business intelligence models for clients. By fine-tuning the most suitable models that align with the business requirements, the company ensures clients derive high-quality and accurate insights in real time. Accenture has a presence in different industries and helps organizations migrate data to the cloud, build modern data platforms, scale AI and ML solutions, and revamp the business process using generative AI. The company also helps businesses in reducing failure rates by guiding them with years of experience in the field. This enables businesses to maximize their performance and ROI. Glassdoor Rating: 3.9 Stars Wipro Wipro offers data, analytics, and intelligence services for businesses to turn their ambitions into reality. The company uses AI technologies to derive maximum insights from data and help clients use these insights to transform their processes. With clients in many countries, the company has the required experience to combine end-to-end critical capabilities and human expertise to deliver the promised results. Be it strategic advisory services or data engineering and management, Wipro ensures to focus on agility, scalability, and flexibility. It works with organizations from numerous industries. EPM automation and modernization, data-driven intelligence, cybersecurity, cloud computing, and sustainability are some other services offered by the company. It believes in connecting art and science, data and people, and intelligence and creativity to help businesses identify market opportunities and gain an edge over competitors. Glassdoor Rating: 3.6 Stars TCS TCS (Tata Consultancy Services) is one of the top data analytics companies offering data management, cybersecurity, IoT (Internet of Things), and enterprise solutions for organizations from several regions. The company helps businesses accelerate growth and results through managed analytics delivered in real time. It builds custom solutions that assist clients in developing new products and services, optimizing internal processes, elevating customer experience, and improving business outcomes. TCS actively manages business data while ensuring the systems are automated to scale as per the client’s needs. It builds a robust data ecosystem for businesses to initiate digital transformation and take advantage of cloud technologies. The company has developed platforms like TCS Datom™, TCS Dexam™, TCS Daezmo™, and TCS business analytics solutions to provide tailored services to enterprises from different sectors. Glassdoor Rating: 3.7 Stars Mu Sigma Mu Sigma is one of the reputed data science companies in the global market. It uses artificial intelligence, machine learning, and computer vision to help clients make data-driven decisions. The company’s intelligent automation models are designed to align with the complexities of the changing market conditions. With experience in many industries, the company has built a model called The Art of Problem Solving System™ for modern businesses. Mu Sigma calls itself a Decision Sciences Company as it goes beyond what most data analytics companies offer. It accelerates the journey from (raw) data to decisions by streamlining the entire process with advanced technologies. All its solutions are suitable for cross-industry applications at various verticals. The company prides itself on offering out-of-the-box solutions to businesses and systemizing decision-making. Glassdoor Rating: 3.3 Stars LatentView Analytics LatentView Analytics is an advanced AI and data analytics solution company that transforms businesses and helps them excel in the digital world. By harnessing the power of data and analytics, the company supported organizations from industries like tech, retail, CPG, industrials, and financial services. Apart from data management and data science, the company offers a range of

Yashica Chopra
November 19, 2024
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Fortune 500 Favorites: Top 10 AI Consulting Services Firms

Artificial intelligence is the key to success, but knowing how to use it makes all the difference. That’s where AI consulting companies help. Here, we’ll discuss the top ten AI consulting services firms that work with Fortune 500 companies around the globe. Artificial intelligence is no longer an option for businesses. It is a must-use technology if organizations want to survive market competition and stay active in this ever-changing global scenario. However, every business, big or small, cannot and may not want to build the AI model from scratch or maintain an in-house team of AI experts. In such instances, it makes sense to hire AI consulting services and partner with reputed service providers to integrate artificial intelligence with business processes and embrace digital transformation. This resulted in various firms offering AI consultancy solutions for startups, SMBs, MSMEs, and large enterprises. Even some of the Fortune 500 Companies prefer to collaborate with AI consulting firms to achieve their goals. So, how big is the AI consulting market? Well, according to BCC Research, the global AI consulting services market is expected to touch $64.3 billion by 2028 at a CAGR (compound annual growth rate) of 34.2%. As per Grand View Research, the global AI market is $196.63 billion in 2023 and is estimated to grow at a CAGR of 36.6% from 2024 to 2030. In this blog, we’ll take a look at the top AI consulting companies that work with Fortune 500 businesses and clients from various other industries. What is AI Consultancy? The biggest barrier to AI adoption is the lack of expertise and the cost of building the models from scratch. Choosing the wrong technologies or approach can lead to more challenges and losses instead of empowering the business. But how can an enterprise overcome these issues without increasing expenses? That’s where AI consulting services come into the picture. An AI consulting company is a service provider that assists various businesses in understanding and adopting AI technologies to achieve their goals. From creating the strategy to ensuring long-term maintenance and support, the consulting company has many roles and responsibilities. However, not all firms offer the same services. For example, some AI consultancy companies are limited to strategy formation or tech support. Some companies offer end-to-end support, including AI product development services and staff augmentation services. The top four (Deloitte, EY, PwC, and KPMG) cater exclusively to MNCs and large enterprises and have premium charges. Fortune 500 Companies may prefer to work with such service providers or opt for other leading AI consulting companies. Top 10 AI Consulting Services Firms DataToBiz DataToBiz is a leading AI product development company offering end-to-end and tailored services for clients from various industries, such as manufacturing, finance, EdTech, healthcare, telecommunication, surveillance, logistics, retail and eCommerce, IT, energy, hospitality, and many more. The award-winning company offers full-scale solutions for businesses to address and overcome challenges. Generative AI, NLP, computer vision, ML modeling, etc., are a part of the company’s AI services. Additionally, DataToBiz also offers custom services for data analytics, data engineering, business intelligence, and IT staff augmentation. It is a reliable and cost-effective company providing AI consulting for MNCs, Fortune 500 firms, startups, SMBs, MSMEs, and large-scale enterprises. The company has ISO certification, along with compliance with SOC 2, GDPR, CCPA, DSS, NIST, and HIPPA. From strategy formation to deployment, integration, and maintenance, the experts from the company handle each process with seamless efficiency. Glassdoor Rating: 4.8 Stars IBM IBM is among the top AI consulting companies in the world and works with Fortune 500 firms, multinational companies, and large enterprises. It offers adaptive solutions for clients from healthcare, manufacturing, IT, finance and insurance, marketing, etc. The company uses an open enterprise-grade AI approach to provide flexibility and scalability for clients while prioritizing safety and compliance with holistic AI. Using its decades of experience in the field, the company has developed various artificial intelligence solutions like Watsonx, Granite, and others. IBM’s AI consulting services help businesses redesign workflows and scale the systems quickly using hybrid cloud technologies. Automation, IT modernization, edge computing, data science, ESG reporting, data management, and cloud security are some of the extensive services offered by the service provider. The company’s generative AI services help different departments like customer service, HR, marketing, finance and accounting, etc. It encourages businesses to become more successful using sustainable processes. Glassdoor Rating: 4.0 Stars Accenture Accenture is an AI services company helping various large enterprises and Fortune 500 firms reinvent their processes with data and artificial intelligence. It partners with leading tech providers like Google AWS, SAP, Oracle, Salesforce, etc., to help businesses build a comprehensive ecosystem to streamline their internal systems. The company’s generative AI consulting services are much in demand in the global market along with other services like cloud computing, cyber security, supply chain, sustainability, Metaverse, finance and risk management, and many more. Accenture has a presence in several industries, such as aerospace, banking, capital markets, energy, consumer goods, public sector, insurance, life sciences, etc. It emphasizes responsible AI for businesses to bridge the gap between intention and execution. The company understands the importance of aligning the AI strategy with business requirements and long-term goals. The services are customized to suit each client’s requirements and scaled for large enterprises across all verticals. Glassdoor Rating: 3.9 Stars LeewayHertz LeewayHertz provides AI consulting services and development solutions for enterprises to amplify operational efficiency and streamline workflows. The company works with clients from finance and banking, manufacturing, retail, insurance, hospitality, healthcare, startups, consumer electronics, and other sectors. It offers AI and ML strategy development services, custom app development, Copilot development, AI integration, enterprise AI development, fine-tuning LLMs, data engineering, and generative AI development services. LeewayHertz has expert AI professionals to provide end-to-end development services for Fortune 500 companies, large enterprises, and mid-scale businesses. It prioritizes speedy development and deployment by following agile methodologies. The company’s advanced tech stack makes it easy to complete and deliver projects within the pre-determined schedule without compromising quality or exceeding

Yashica Chopra
November 03, 2024
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13 Staff Augmentation Service Models to Consider in 2025

Staff augmentation is useful, cost-effective, and a scalable solution for businesses to expand their teams whenever necessary. Here, we’ll discuss the different types of staff augmentation services and how these can help in tailoring the IT staffing strategy in a business. There’s a high demand for information technology (IT) services in various industries. Businesses from around the globe have been adopting new technologies to revamp their processes and compete in changing market conditions. Statistics show that the IT market size has grown from $8508.63 billion in 2023 to $9039 billion in 2024 at a CAGR (compound annual growth rate) of 6.2% and is expected to reach $12417.21 billion by 2028 at a CAGR of 8.3%. In such instances, the demand for IT professionals from various domains has also increased. Programmers, engineers, data analysts, data scientists, software developers, AI and ML experts, etc., are also being hired by non-IT businesses. However, not all enterprises follow the same hiring patterns. Instead of recruiting professionals permanently, many organizations are opting for outsourcing, managed services, or staff augmentation services. In this blog, we’ll talk about staff augmentation and the various types of staff augmentation services available in the market. What are Staff Augmentation Services? Simply put, staff augmentation is the process of temporarily using professionals from outside the establishment to work with your existing teams on a particular project. They augment your internal team capacity and capabilities to help you achieve your goals. IT companies offer staff augmentation services to help other IT and non-IT businesses access talent and technology through cost-effective means. Rather than spending money on full-scale recruitment for temporary jobs, you can sign a contract with a staff augmentation company to quickly hire as many experts as you want and pay them only for the project/ duration. What is an Example of Staff Augmentation? For example, a manufacturer wants to digitally transform the systems and set up IoT (Internet of Things) devices with factory equipment for data collection. The manufacturer can hire IT staff augmentation services to build a team of programmers and data analysts to handle the project. The selected external experts will collaborate with the enterprise managers to understand the requirements and deliver the results. The manufacturer will have to pay salaries only for the duration of the project (or choose a relevant plan to pay for the services). Most staff augmentation service providers can build teams in 48-72 hours and they start working on the project in around a week. This reduces the time to market and eliminates unwanted expenses for the manufacturer. Types of Staff Augmentation Services Staff augmentation services can be truly diverse and tailored to suit your business requirements at different times. This variety has made it a popular staffing method in the global market. Traditional Staff Augmentation Traditional staff augmentation involves hiring experts based on the problems faced by in-house teams. The experts usually work on-site and sign a contract to remain part of the team until the issue is sorted. It’s pretty much like a contract job, except the access to talent is limited to the region. Offshore Staff Augmentation Offshore staff augmentation is almost the opposite of the traditional model, as you can access experts from around the world to work on your project. The temporary employees belong to another country (which is usually across the ocean, hence the term offshore) and work from their locations remotely. Managing time zones and cultural differences can be a concern if you don’t partner with reputed service providers in offshore staffing. Onshore Staff Augmentation Onshore staff augmentation is similar to the traditional model except that the experts can belong to neighboring countries as well. You have access to a wider talent pool but not to the extent of the offshore model. For example, US companies can hire external employees from Canada, Mexico, or Latin American countries. Remote Staff Augmentation As the name suggests, the experts will work remotely and collaborate online to interact with your in-house employees. They can belong to the same region or live on the other end of the world. The services are offered remotely so that they don’t have to visit your office to get the job done. This method is cost-effective, though it needs a reliable internet network and wider bandwidth. Agile Staff Augmentation Agile staff augmentation involves building a team of experts from various domains to manage a project from beginning to end. For example, in analytics staff augmentation, the team will consist of a programmer, AI engineer, data analyst, data engineer, data scientist, business intelligence analyst, etc., to build, deploy, integrate, and maintain the data architecture. The teams are created based on your requirements. Resource Augmentation Resource augmentation combines staff augmentation and other resources. It is a model developed to help businesses bridge the resource gap in their organizations without spending too much money on building everything from scratch. The resources offered by the service provider include talent, technology, infrastructure, etc. While it is similar to outsourcing, resource augmentation provides more flexibility and can be for the short term. Temporary Staff Augmentation As the name suggests, temporary staff augmentation services are time-bound and used for short-term requirements and simple projects that can be completed quickly. It is a great model to address the immediate needs and concerns in an establishment. Sometimes, external experts are brought in during the last phase of a project to sort out the issues and release the product into the market. Project-based Staff Augmentation Project-based staff augmentation involves hiring experts for the entire project. Typically, team augmentation services are project-based since complex projects require more team members and diverse talent. You can easily scale the teams without incurring extra overhead costs or delaying the project to wait for new additions. The project-based model can be for the short-term, mid-term, or long-term. Long-term Staff Augmentation Long-term staff augmentation involves hiring external talent to work with your businesses for an extended period, which could be several months or a few years. Organizations prefer the long-term

Yashica Chopra
November 03, 2024
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9 Building Blocks of Data Engineering Services – The Fundamentals

Data engineering is the key for businesses to unlock the potential of their data. Here, we’ll discuss the fundamentals aka the building blocks of Data Engineering Services, and the role of data engineering in helping businesses make data-driven decisions in real time. Data engineering services are gaining demand due to digital transformation and the adoption of data-driven models in various business organizations. From startups to large enterprises, businesses in any industry can benefit from investing in data engineering to make decisions based on actionable insights derived by analyzing business data in real-time. Statistics show that the big data market is expected to reach $274.3 billion by 2026. The real-time analytics market is predicted to grow at a CAGR (compound annual growth rate) of 23.8% between 2023 and 2028. The data engineering tools market is estimated to touch $89.02 billion by 2027. There’s no denying that data engineering is an essential part of business processes in today’s world and will play a vital role in the future. But what is data engineering? What are the building blocks of data engineering services? How can it help your business achieve your goals and future-proof the process? Let’s find out below. What are Data Engineering Services? Data engineering is the designing, developing, and managing of data systems, architecture, and infrastructure to collect, clean, store, transform, and process large datasets to derive meaningful insights using analytical tools. These insights are shared with employees using data visualization dashboards. Data engineers combine different technologies, tools, apps, and solutions to build, deploy, and maintain the infrastructure. Data engineering services are broadly classified into the following: Azure Data Engineering Microsoft Azure is a cloud solution with a robust ecosystem that offers the required tools, frameworks, applications, and systems to build, maintain, and upgrade the data infrastructure for a business. Data engineers use Azure’s IaaS (Infrastructure as a Service) solutions to offer the required services. Finding a certified Microsoft partner is recommended to get the maximum benefit from Azure data engineering. AWS Data Engineering AWS (Amazon Web Services) is a cloud ecosystem similar to Azure. Owned by Amazon, its IaaS tools and solutions help data engineers set up customized data architecture and streamline the infrastructure to deliver real-time analytical insights and accurate reports to employee dashboards. Hiring certified AWS data engineering services will give you direct access to the extensive applications and technologies in the AWS ecosystem. GCP Data Engineering Google Cloud Platform is the third most popular cloud platform and among the top three cloud service providers in the global market. From infrastructure development to data management, AI, and ML app development, you can use various solutions offered by GCP to migrate your business system to the cloud or build and deploy a fresh IT infrastructure on a public/ private/ hybrid cloud platform. Data Warehousing Data warehousing is an integral part of data engineering. With data warehousing services, you can eliminate the need for various data silos in each department and use a central data repository with updated and high-quality data. Data warehouses can be built on-premises or on remote cloud platforms. These are scalable, flexible, and increase data security. Data warehousing is a continuous process as you need to constantly collect, clean, store, and analyze data. Big Data Big data is a large and diverse collection of unstructured, semi-structured, and structured data that conventional data systems cannot process. Growing businesses and enterprises need to invest in big data engineering and analytics to manage massive volumes of data to detect hidden patterns, identify trends, and derive real-time insights. Advanced big data analytics require the use of artificial intelligence and machine learning models. 9 Building Blocks of Data Engineering Services Data Acquisition Data ingestion or acquisition is one of the initial stages in data engineering. You need to collect data from multiple sources, such as websites, apps, social media, internal departments, IoT devices, streaming services, databases, etc. This data can be structured or unstructured. The collected data is stored until it is further processed using ETL pipelines and transformed to derive analytical insights. Be it Azure, GCP, or AWS Data Engineering, the initial requirements remain the same. ETL Pipeline ETL (Extract, Transform, Load) is the most common pipeline used to automate a three-stage process in data engineering. For example, Azure Architecture Center offers the necessary ETL tools to streamline and automate the process. Data is retrieved in the Extract stage, then standardized in the Transform stage, and finally, saved in a new destination in the Load stage. With Azure Data Engineering, service providers use Azure Data Factory to quickly build ETL and ELT processes. These can be no-code or code-centric. ELT Pipeline ELT (Extract, Load, Transform) pipeline is similar but performs the steps in a slightly different order. The data is loaded to the destination repository and then transformed. In this method, the extracted data is sent to a data warehouse, data lake, or data lakehouse capable of storing varied types of data in large quantities. Then, the data is transformed fully or partially as required. Moreover, the transformation stage can be repeated any number of times to derive real-time analytics. ELT pipelines are more suited for big data analytics. Data Warehouse A data warehouse is a central repository that stores massive amounts of data collected from multiple sources. It is optimized for various functions like reading, querying, and aggregating datasets with structured and unstructured data. While older data warehouses could store data only tables, the modern systems are more flexible, scalable, and can support an array of formats. Data warehousing as a service is where the data engineering company builds a repository on cloud platforms and maintains it on behalf of your business. This frees up internal resources and simplifies data analytics. Data Marts A data mart is a smaller data warehouse (less than 100GB). While it is not a necessary component for startups and small businesses, large enterprises need to set up data marts alongside the central repository. These act as departmental silos but with seamless