Top Data Analytics Companies and Software Tools

Top Business Intelligence Companies & Software Tools

Data analytics is more important than ever.

If you want to be competitive and successful in today’s landscape, you need to be able to gather important data, analyze that data, and use your analytics to gain insights that drive your business forward.

That’s a lot of buzzwords. But they convey a simple truth.

You need data analytics and business intelligence for your company to survive.

Thankfully, there are more data analytics companies and more data analytics software tools than ever before.

So what are the best options to choose from?

And how can you choose the best fit for your organization?

The Top Data Analytics Companies

These are some of the best data analytics companies in the world:

Top Data Analytics Companies

  1.   Oracle. Oracle was founded in 1977, making it one of the oldest and best-known entries on this list. With more than 164,000 employees, Oracle offers robust data analytics software that can incorporate data streams from both Oracle and non-Oracle sources. It has kept pace with technological development, incorporating ML and AI into its services – and is still one of the biggest data analytics companies in the world.
  2.   Tableau. One of the biggest data analytics companies in the U.S., Tableau specializes in offering visual tools that can help you organize and visualize your data. Focusing on business analytics and intuitive visualization, Tableau has the power to help you solve almost any conceivable business challenge. Its tools are also highly effective in drawing in data from multiple different sources simultaneously.
  3.   Accenture Analytics. Accenture Analytics is a Fortune Global 500 company that offers services including app development, SAP, software development, blockchain, supply chain, and more. It’s currently home to more than 492,000 employees and thrives in 200 cities in more than 120 countries. It has 1,800 dedicated data analysts and specializes in machine learning and artificial intelligence (AI) powered analytics services.
  4.   Vention. Based in the U.S., Vention offers a range of data analytics services including real-time and predictive data analytics. With more than 20 years of operating history and 1,600 excellent employees, Vention primarily serves mid- to large-sized businesses. Vention employs experts in blockchain, AR/VR, AI, and big data, and has helped clients see an average of $600,000 in annual savings as a result of their efforts.
  5.   Manthan Systems. Based in India, Manthan Systems has been serving large retail organizations since 2003. Offering a variety of big data and AI-powered solutions, Manthan Systems helps customers in food service, convenience, eCommerce, grocery, fashion, and apparel industries – and more.
  6.   Fractal Analytics. Fractal Analytics, with more than 20 years of operation, is based in the U.S., but with offices in the U.K. and India. Using AI and advanced data analytics tools, Fractal Analytics serves customers in healthcare, technology, retail, and many other industries. It has multiple subsidiaries, including and
  7.   LatentView Analytics. LatentView Analytics has offices all over the world and was named Analytical Solutions Provider of the Year by Frost and Sullivan in 2015. It offers exhaustive big data and predictive analytics solutions and has its own in-house research and development lab called IdeaLabs. It serves businesses across many industries, including retail, consumer goods, technology, and financial services.
  8.   SG Analytics. SG Analytics, based in India, was founded in 2006. It now provides data analytics services including data analysis, market research, and more. SG Analytics has won multiple awards for its status as an employer and is known for its signature methodologies for data collection, aggregation, and insight generation.
  9.   Infogain. Infogain, formerly known as Absolut Data, is headquartered in San Francisco and is celebrated as a top company in market research, CRM analysis, big data analytics, and visualization. It uses a signature approach to advanced analytics that combines aspects of new technology and complex data. Infogain also utilizes powerful AI software to help solve previously unsolvable problems.
  10.   Mu Sigma. Mu Sigma, based in the U.S., was founded in 2004, primarily offering data analytics and management consulting. With more than 3,500 employees, this company offers a range of tools and supportive services to help its clients gather and analyze data. Its primary industries served include retail, healthcare, financial services, and telecom.

The Top Data Analytics Software Tools

In addition to the tools created and supported by the data analytics companies mentioned above, these are some of the top data analytics software tools currently available:

Top Data Analytics Software Tools

  1.   Microsoft Power BI. Microsoft Power BI is designed as a business intelligence platform that can support dozens of different sources of data. With it, you can create your own dashboards, visualizations, and reports – and even group dashboards and reports together for convenience. Automated machine learning models are also available, as are integrations with Azure Machine Learning.
  2.   SAP BusinessObjects. SAP BusinessObjects includes a diverse suite of different business intelligence applications, designed to assist with data discovery, analytics, and of course, reporting. Designed for people with limited BI and data analytics experience, BusinessObjects integrates directly with Microsoft Office – and excels in the realm of predictive analytics.
  3.   Sisense. Sisense is equally useful for experienced and inexperienced data analytics alike, and can help to visualize almost any type of business data. Primarily relying on drag-and-drop style tools, Sisense is highly usable and intuitive – and it can work faster than many tools because of its CPU caching optimization.
  4.   TIBCO Spotfire. TIBCO Spotfire makes use of natural language-powered searching and AI-powered data analytics to deliver an excellent data analytics experience all-around. With visualization tools that work on mobile and desktop seamlessly, users can build perfect predictive analytics models that serve their goals.
  5.   Thoughtspot. Thoughtspot is another data analytics platform that integrates multiple sources of data simultaneously. Using natural language searches, users can harness the full power of this AI system and discover insights that can help them identify patterns – and eventually make better decisions. Users can also employ automation to join tables and eliminate data silos.
  6.   Qlik. Qlik offers both cloud and on-premises deployment for its comprehensive data analytics and business intelligence platform. With strong potential for data discovery and data exploration, both technical and non-technical users can find value in it. Drag-and-drop interactions make it easy to create new modules as well.
  7.   SAS Business Intelligence. SAS Business Intelligence is another suite of tools designed to facilitate smoother self-service analytics. It’s designed to be a flexible and comprehensive platform, so it’s a bit more expensive than other tools on this list – but businesses with significant data analytics demands may find it more than worth the extra price.
  8.   Google Data Studio. Google Data Studio relies on helpful dashboards and visualizations to make data much more intuitive and accessible. It integrates with most Google products, including Google Analytics and Google Ads, and is completely free – though it’s not designed to be fully comprehensive as a data analytics solution.
  9.   Redash. Redash was created to be minimalistic and cost-effective, but it’s surprisingly good at creating data visuals. The code is completely open-source, which means you can create a custom branch of your own if so desired. Otherwise, you can take advantage of the existing interface to handle nearly all of your data analytics needs.
  10.   Metabase. Another open-source tool, Metabase is completely free – and helps even non-technical users ask the right questions about their data. It’s highly useful for things like filtering and aggregation, and technical users can go straight to raw SQL if desired. It also has strong support for integrating with external systems.
  11.   IBM Cognos. IBM Cognos is another strong business intelligence platform that uses the latest AI to analyze large sets of data. With automation, customization options, and easy processes for cleaning and aggregating data sets, it allows for convenient experimentation and data refinement.
  12.   Chartio. Through Chartio, users get access to a complete self-service business intelligence system. You can incorporate data from multiple sources, import data from simple spreadsheets, and even execute queries without utilizing SQL syntax.
  13.   Domo. Finally, we have Domo, which boasts more than 1,000 individual integrations known as connectors to help users transfer data to and from other sources. Domo also facilitates the development of new connectors and other tools for seamless data transfer, modification, experimentation, and visualization. It’s a single platform with both a data warehouse and ETL software.

Choosing the Right Data Analytics Solution

There are so many data analytics solutions to choose from, including both data analytics firms and data analytics software tools.

How can you choose what to write for your business?

First, consider whether you want to work with a data analytics firm, incorporate data analytics tools, or both. Companies without much internal support for data analytics are often best served by working with third party data analytics specialists. However, data analytics tools also cover a range of needs, both for technical data analytics experts and non-technical laypeople.

No matter what, you’ll want to consider the following:

  •       Features and services. What are the main features available in this data analytics software product? Alternatively, what services are available through this data analytics provider? Individual business needs vary, so make sure your core needs are being addressed.
  •       Industry and application focus. Some firms and tools are designed to serve a specific industry, or a specific selection of industries. Additionally, some tools and firms only exist for businesses of a certain size. Depending on your needs, it may make sense to work with a specialist in your area, or you may prefer working with a generalist.
  •       Usability/collaborative potential. Data analytics shouldn’t be a massive headache. You need to find a tool that’s highly usable or a partner who’s easy to work with if you want the smoothest possible experience. Always utilize free trials for data analytics tools before integrating them and ask lots of questions of your data analytics firm before signing a contract. Look for partners who are transparent, honest, and openly communicative; otherwise, your data analytics partnership runs the risk of eventually breaking down.
  •       Philosophy and approach. While there are some golden rules when it comes to gathering and analyzing data, there’s plenty of room for differences in philosophy and methodology. It’s important that you find a tool or data analytics service provider with a philosophy and approach that makes sense to you – and one that’s in perfect alignment with your business philosophy and goals.
  •       Proven results. Ideally, you’ll be able to prove the expertise and value of your chosen solution. Are there lots of case studies and examples of successful clients? Are there ample good reviews and testimonials? Has this organization been able to help organizations like yours? Some data analytics companies attempt to calculate how much money they save their clients or how much they boost revenue; these objective metrics are exceedingly important in determining whether it’s worth moving forward with a given option.
  •       Pricing. Of course, you’ll also need to think about pricing. The tools and business services on this list range from totally free to very expensive, but not all of them have the same value to cost ratio or the same level of support. Consider setting a budget for your data analytics needs, then finding the best available tool within that budget range.

Building a Custom Solution

In this article, we’ve covered some of the top data analytics companies and software tools currently available. We’ve also helped you understand how to pick the right data analytics and business intelligence solutions for your business.

But we also understand that every business is totally unique – and not all businesses or industries are adequately served by the tools and data analytics firms currently on the market.

If you’re looking for something unique, something better suited to your type of business, or something more perfectly aligned with your budget, building a custom solution could be the answer.

And if that’s the case, you’re in the right place.

At, we have a dedicated team of talented software developers and data analytics specialists who can help you build almost any conceivable solution. If you’re ready for a free consultation, contact us today!

Chief Revenue Officer at Software Development Company
Timothy Carter is the Chief Revenue Officer. Tim leads all revenue-generation activities for marketing and software development activities. He has helped to scale sales teams with the right mix of hustle and finesse. Based in Seattle, Washington, Tim enjoys spending time in Hawaii with family and playing disc golf.
Timothy Carter