Big Data, Big Tools

With Big Data comes big tools. Data sets have grown dramatically in the past five years and continue to quickly expand. A decade ago Big data used to mean thousands of records, but now Big Data encompasses millions and billions of number sets. With data this big we need to use some powerful tools in order to perform proper analysis. Below is a review of some of the popular tools businesses are using to analyze their data.

SAS
SAS is a powerful program that can do a lot of fun things. Using SAS Enterprise Miner allows users to perform association, linear regression, cluster analysis, uplift and more within minutes. Setting up a workflows and creating models are simple once familiarity with the platform is established. Filters can be added to partition the data and separate out the portions of data that are specifically needed to solve a problem. This can be extremely useful for big data sets with thousands of variables. The results can be tricky to decipher, sometimes different drop-downs need to be used to switch views or discover hidden pieces of data results.

SAS Visual Analytics is an amazing tool. Variables appear down the left hand column of the screen and users can literally drag and drop two variables into the work area to produce a graph or chart of the data. Autocharting is a feature that automatically selects the best type of chart or graph for the data variables a user drags into the workspace. The software is able to analyze the relationship between the types of data being used and instantly produces a visual result. The intuitive autocharting feature definitely makes the program more user friendly. The filers are intuitive and drilling down to reach the correct data variable is less complicated than in SAS Enterprise Miner.

Excel Miner 
Even Microsoft is capitalizing on the data mining trend. Excel Miner is an extension of Microsoft Excel that allows users to work with sets of data that would normally not be compatible with the regular program. The Excel Miner extension is simple enough to install, but the program can be slow when taking in larger data sets. Excel Miner allows users to perform some of the same types of analysis as they would in SAS, but it takes a lot longer to perform some of the same tasks. Running regression in Excel Miner may take forty five minutes to set up, where you could run the data set in SAS Enterprise Miner and be finished in twenty five minutes.

Tableau
As someone who appreciates design and user experience, Tableau has the most aesthetically pleaseing interface of the tools I have used. The navigation is clear, the layouts are clean and the icons make tools easy to distinguish and easy to find. Tableau’s drag and drop features are easy to navigate. Dragging elements from data sets into the “column” and “row” features set up quick, comprehensible charts. Tableau’s map feature also allows users to show metrics by location, and can even filter by color density. The dashboard feature allows users to lay out charts, maps, tables and data. There are features that can also make dashboards interactive, so hovering over an area of the dashboard can isolate certain metrics to give the end user a better idea of individual performances. The interfaces are already perfectly designed and easy to adjust to fit brand guidelines and can please everyone from a CMO to a creative director. If you care about aesthetics and usability, Tableau is the best option.

As Big Data gets bigger and bigger, new tools will be released and tried and true tools will continue to evolve to keep up with the demand. There are quite a few Big Data analysis tools on the market right now, but SAS, Excel Miner and Tableau are user-friendly tools that are powerful enough for experts and easy enough to navigate for beginners.