Getting started with data analytics can be a daunting task. You might feel overwhelmed with all the data out there and the tools available to process, extract and visualize it. That’s why we decided to do an overview of some of the best data analytics software available today and provide you with a detailed table of contents that will get you straight to what you need.
Data analysis software is the best way to make sense of even the most complex datasets. It can help you to analyze trends, find insights and make better business decisions.
Chartio
Platform: Chartio
Description: Chartio is a cloud-based data discovery platform that lets you create charts and interactive dashboards. The product features a proprietary, visual version of SQL that enables any user to explore, transform and visualize data via a flexible drag-and-drop interface. There is no need to build data models in advance. Chartio includes a set of pre-built connections to data sources like Amazon Redshift, Google BigQuery and Snowflake, while also enabling direct access to CSVs and Google Sheets.
Domo
Platform: Domo
Related products: Domo Everywhere, Domo integration Cloud
Description: Domo is a cloud-based, mobile-first BI platform that helps companies drive more value from their data by helping organizations better integrate, interpret and use data to drive timely decision-making and action across the business. The Domo platform enhances existing data warehouse and BI tools, and allows users to build custom apps, automate data pipelines, and make data science accessible for anyone across the organization through automated insights that can be easily shared with internal or external stakeholders.
Hitachi Vantara
Platform: Pentaho Platform
Related products: Lumada Data Services, Pentaho Data Integration
Description: Hitachi’s Pentaho analytics platform allows organizations to access and blend all types and sizes of data. The product offers a range of capabilities for big data integration and data preparation. The Pentaho platform is purpose-built for embedding into and integrating with applications, portals, and processes. Organizations can embed a range of analytics, including visualizations, reports, ad hoc analysis, and tailored dashboards. It also extends to third-party charts, graphs and visualizations via an open API for a wider selection of embeddable analytics.
BigID
Our score: 8.7User satisfaction: 97%
A modern data intelligence platform that enables enterprises to discover, manage, and protect data critical to their business. Powered by machine learning, the software allows for more efficient, consistent, and scalable data governance across any data in the cloud or data centers. It makes it possible for companies to know their data and take action for protection, privacy, and perspective.
ThoughtSpot
Key Insight: While not as well known as some other data analytics software vendors, ThoughtSpot offers a next-generation “search first” tool that earns it a berth as a leader in the market.
ThoughtSpot offers any number of compelling features, particularly an AI-based recommendation system that leverages crowdsourcing. Additionally, sources for its query options range from a legacy provider like Microsoft to a “new kid on the block” like Snowflake.
But most attractive of all, ThoughtSpot’s calling card in a crowded market is its search-based query interface. Users can input a complex analytics query – by typing or speaking – and the ThoughtSpot platform uses augmented analytics to offer insight. Impressively, it can handle large data queries, with many users sifting through more than a terabyte of information. All of this is accomplished – from comparative analysis to anomaly detection – with no software code required. So business staff can data mine without the help of experts.
Pros:
- The search interface allows easy queries of complex questions, analyzing billions of data rows with artificial intelligence.
- Founded in 2012 as a growing company, the company has ridden the wave of enterprise analytics to a solid niche in the analytics sector.
- Well regarded for its ability to scale and handle ever-larger query loads.
Cons:
- Without the large product portfolio of some vendors, users will need to bring their own related tools, like data preparation applications.
MicroStrategy
Key Insight: In a bold move, MicroStrategy envisions itself as the foundation of enterprise analytics, by connecting various competing platforms into a unified system.
In a highly competitive data analytics market, where each vendor is trying to top the others, MicroStrategy seeks to join them together. Its platform includes API connectors that join competing platforms while – of course – using MicroStrategy as the unifying layer. In a related technique, the company connects all business content from browser-based systems, like CRM and ERP (and competing analytics software), and then offers it as an easy-to-consume analytics dashboard.
As soon as a user moves their mouse over a link, the data appears – offering updated, real-time data insights through the workday.
Additionally, users who can code can leverage MicroStrategy to quickly insert or update a diverse array of data sources from mobile or across the Internet. This easy update from multiple sources plays into MicroStrategy’s “connector” strategy and is well regarded in the data analytics sector.
Pros:
- MicroStrategy’s Hyperintelligence linking technology is an innovative twist that may launch it into a leading position in the years ahead.
- Well respected for the stability of its platform, with little or no problem with bugs or downtime.
Cons:
- Does not have a high profile in the data analytics market.
Sisense
Key insight: A sophisticated, forward-looking platform that is well-suited to complex, ongoing data processing – Sisense is great for the power user, but not so much the untrained staffer.
It’s clear that Sisense is committed to a forward-looking data analytics platform. The company reimagined and then largely rebuilt its platform to leverage the advantages of a cloud-native infrastructure.
Among these advantages is great scalability. Sisense drives cloud-native applications at scale in tandem with container technology. As your data needs grow, the platform will surely keep up in the years ahead as cloud platforms get faster and more flexible.
To drive still greater speed and performance, Sisense’s ElastiCube uses its own caching engine, which deploys in-chip and in-memory data crunching. Elasticube boosts the platform’s augmented data prep features. Additionally, Sisense acquired Periscope Data to increase its upper-level data processing features.
Pros:
- Strong support for cloud-native applications.
- Proprietary caching engine enables faster speeds.
- Able to handle a wide array of difficult enterprise analytics workloads.
Cons:
- Geared for advanced users, especially data scientists, instead of off-the-cuff business queries.
Conclusion
The Best Data Analytics Software is the only software that gives you all the tools you need to grow your business. The Best Data Analytics Software provides support for the Microsoft SQL Server, Hadoop, Amazon RDS, Google BigQuery and more. Ever wonder what kind of data analytics software is out there? Well it turns out there are some pretty amazing data analytics software titles out there. We’ve rounded up some of the best data analytics software on the market today!