Data analytics software enables human decision makers to go in and examine raw data, to make all sorts of conclusions about the realities around that data. Enterprise users rely on data analysis software to get actionable results out of big data, and to effectively use existing data assets. Here are some of the most popular and interesting data analytics choices on today’s market.
With the Sisense platform, even less tech-savvy users can build interactive dashboards and come up with useful results from raw data. This vendor is offering gives users different dashboard views and transparent and straightforward charting and graphing tools where users can take advantage of geographical maps to view locational data, or analytical tools for key performance indicators, or scatter plots or pie charts to show different data results in a compelling visual way. User interface tools are also convenient with drag-and-drop functionality for a user-friendly environment.
One of the compelling features of the data analytics platform ITALASSI is its ability to model variables with regression. This piece of freeware takes different regression models and displays them in three dimensional graphs with color-coding. This enables users to look at the raw data on the intersection of two variables. This advanced statistical software can be part of a greater enterprise solution.
Another platform called Waffles comes with machine learning functionality built in. In addition to straightforward tools for data mining and predictive modeling, users can take advantage of another type of support included in Waffles, which rests on machine learning principles — with this functionality, the program ‘plugs in’ missing values to show a more concrete record representing sparser or more fuzzy data sets. Users have called Waffles a more creative take on data science — this C++ based collection of command-line interface tools is available at SourceForge.
In some ways, the Gephi platform is similar to some of the more modern aspects of Internet-based research or hypertext exploration.
It’s an open source tool, with interesting visualization features. Users can get real-time analysis, and link analysis — which maps relationships between objects in a network – think of the data linking properties of JSON and the way logical networks are mapped to the World Wide Web, and you have some idea of how certain functions of this platform work. Users have billed this system as a set of “social data connectors” and applauded the functionality of the platform for freeing data to flow.
Scratch the surface of the Open Refine data analysis tool set, and you’ll see that it was formerly known as Google Refine. Industry experts suggest that Google got tired of supporting this analysis tool, and didn’t link it into the community of cloud-based Google applications. For whatever reason, Open Refine is now run by its community of users. That doesn’t take away from its use as a mature data analytics platform — Open Refine has a competitive dashboard that shows cluster information, provides filters and partitions for data, links different data sets, and uses functions like named entity extraction to build sophisticated data results that can be useful for enterprise teams.
A more playful take on data analytics is presented by Orange, a platform which “makes data mining for full and fun.” With data visualization tools, the graphic user interface of Orange combines proprietary data analysis methods with user-friendly controls. Its build makes Orange a favorite at schools, where educators and students may use it to come up with all sorts of results for research projects. Like other platforms, Orange supports scatter plots, heat map charting, classification trees, hierarchical clustering and more. Unlike some other platforms, it does it all in style, with straightforward results that humans can read easily.
As part of a group of popular enterprise solutions developed by Tableau, this data analytics option offers a particular focus data analysis application with drag-and-drop features, sharing and social media features, and much more. Users can connect to Google Sheets, use data interpretation tools, or join and unify data sets to come up with visual results. There is also mobile support for this platform and a vibrant community of users, as well as live training available on the website.
Bolstered by name recognition and a significant enterprise software market share, SAP tends to go big with its enterprise products — it does the same thing with SAP Lumira, billing this application as “superior data visualization” and uncovering many of its unique tools such as its drag-and-drop interface, charting tools, and resources for “uncovering hidden trends” in raw data. Users cite a low learning curve, ease-of-use and versatility in this popular data analytics offering.
This Fortran and C based data analysis system may not look like much, but it was developed at the CERN laboratories, and has been useful for different kinds of highly technical research and presentations for years. Check it out for a “retro” data analysis experience that still packs a punch.
The ROOT data analysis system, also pioneered at CERN, was made to handle work on particle physics, but it can just as well be applied to other uses. Part of ROOT’s appeal is its visual platform – for a C based program, this one can present raw data in some pretty sophisticated ways.
IPython for Data Analysis
This tool set was made to support the Python programming language. It runs on a shell model and includes a web-based notebook and other tools. This is a good tool set for users who are not tethered to Windows and some of the more conventional end-user formats of Microsoft’s operating systems.
Look at any of these excellent data analysis tools to support crunching enterprise data in a business architecture.