Big Data or more precisely Big Data analytics has almost become the most popular tech word in regard to using ever increasing bulk of digital data for multifarious business and user objectives. Making the gigantic volume of classified and unclassified data sets from diverse spheres work to produce insights and actionable analytical outcomes is what Big Data analytics tools are all about and a large pool of new startups and big IT houses are already making the scene look enough competitive with these tools and applications for diverse real life uses continuing to show up. From open source Big Data analytics tools like Apache Hadoop or Cloudera Impala to Attensity or Clabridge as text analytics tools for Big Data to Pentaho Business Analytics for generating reports and business insights, there are multitude of Big Data analytics tools that are going to make analysis and data processing easier than ever before. Here are our picks of top 10 Big Data analytics tools.
Unquestionably if you consider high volume data processing platform with thousands of applications and operational users in business environment there can hardly be any Big Data analytics tools that can be compared with this. It is ideal for large scale data warehousing and real time analytics feedback. For instance in a typical call center environment where the employees need to track caller history or previous call details promptly as and when it is required, such data powerhouse with multitude of applications for real time feedback is ideal for making the operation smooth and clutter free.
Cloudera Impala is the analytics tool for real time SQL queries. Sitting inside your Hadoop cluster it listens to all sorts of queries and with appropriate execution plan and with parallel processing with other nodes in the cluster it comes out with real time low latency SQL queries with deep insights into Big Data. If Cloudera as a Big Data startup already reached up the star ranks beside world's most formidable IT companies, this analytics tool had a lot of contribution behind the scene.
In our venture to present here the top 10 Big Data analytics tools we cannot omit this superb innovative data analytics tool that already won many accolades besides being a clear leader with $ 186 revenue from the business. Splunk is known to process machine generated data across various computing gadgets and personal computers to produce diverse range of insights for different end user purposes. With more than 5200 licensed customers across 74 countries Splunk is one of the leading names among Big Data tools.
Amazon Redshift is the flagship Big Data analytics tools from Amazon that like its other products in the Big Data space is going to earn good client appreciation in the near future. This highly scalable data warehousing service that is about to launch early next year (just a few months from now) is going to lead the way in sophisticated scaling up of capacity in data warehousing and management.
Recently the brand attracted huge venture capital funding from top IT corporations around the globe that amounts to more than $150 million, a sure indication of its value proposition in Big Data space. Though the software is free and open source, in respect of providing data stream integration for certain applications it proved really easier and faster compared to most of the other Big Data analytics tools and that precisely drawing the attention of world's who's who in IT business to it.
Though the brand is already a seasoned player in the space of data analytics, the recent launch of advanced predictive analytics tools by the company again made it come to focus. The second generation H2O machine learning and predictive analytics engine which is named as 'Fluid Vector' release can perform complex, parallel and distributed algorithms on big volumes of data at a speed that is at least 100 times faster than other so called predictive data analytics tools. The software which is coming to address broader audience or users is certainly going to champion the speed in performing complex analytical tasks for array of real life and business uses.
Smarter compressed storage of big volumes of data, faster querying speed in analytical applications, low maintenance while retaining high performance in comparison to other relational databases, supporting parallel processing and above all the innovative team of HP working behind its constant upgrading and development - these all perfectly explains the brilliance of this hugely popular tool. The scalability features of this tool made it a preferred tool for high end e-commerce and data intensive digital marketing customers like AOL, Twitter and Groupon. The tool also supports HP's cloud service application.
Among the top 10 Big Data analytics tools certainly you need to name at least one tool that is specific to business use. Pentaho Business Analytics tool that is mainly focused on addressing the barriers of obstacles that any business organization faces in respect of getting full potential value of the data. It includes an array of diverse range of tools to analyze, explore, visualize, find loopholes and opportunities, prepare report and finally predict. The tool which is easy to maneuver can be a perfect accompany to everyone (either a developer or marketer) within an organization for getting maximum value from data.
This is probably the smartest machine learning and pattern discerning application for everybody's use of data analytics. Putting the machine learning into work the tool provides you enough pattern types that automatically feed the answers into the application. From spam detection to analyzing sentiments to engine recommendation, it provides detailed step by step instructions for all these models.
MicroStrategy has recently come into the Big Data space by upgrading its line of BI software with the inclusion of Big Data analytics tools. The flagship BI application of the company remodeled as MicroStrategy Analytics Platform is allowing the analysts to easily access and work on large data sets through a desktop application. The new enterprise software from the company allows the users to combine data from multiple sources which is a feature called 'data blending' as per the company.