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  1. What is Big Data analytics?

The meaning of big data influences the key to understanding big data analysis. By Gartner IT Glossary, Big Data is high-volume, high-speed and high-variety information resources that request cost effective, innovative types of information processing for improved insight and decision making.

Volume points out the amount of data. Numerous factors are adding to high volume: sensor and machine-created data, social media, networks and much more. Enterprises are flooded with terabytes and, progressively, petabytes of big data.

Variety points out to the quantity of types of data. Big data expands beyond structured data such as strings, dates and numbers to incorporate unstructured data such as audio, video, text, click streams, 3D data and log files.

Velocity points out to the speed of data processing. The velocity at which data streams in from sources for example mobile devices, clickstreams, high-frequency stock trading, and machine-to-machine processes is gigantic and constantly fast moving.

  1. What are the benefits of big data analytics tools?

According to a survey of 540 endeavor decision makers involved in enormous data purchases by Webopedia’s parent organization QuinStreet, about half of all respondents told that they were implementing big data and analytics to improve client retention, help with product advancement and gain a competing advantage. These are just a few of the noteworthy insights made achievable by big data analytics tools. Whether a company is looking to boost sales and marketing outcomes, optimize operational efficiency, uncover new revenue opportunities, improve customer service, reduced risk, or drive different business results, big data insights can assist.

3. What are the use cases for big data analysis?

big data analytics

Img-source: www.qubole.com

  1. How can you support big data analytics?

A wide range of solutions are required to support the variety of big data use cases. From plain spreadsheets to advanced analytics, you can provide effortless integration to centrally analyze your data and marketing solutions to analytics engines, all in one spot.

Spreadsheets and Analytics Tools: With the help of ODBC connectors, your clients can connect to Microsoft Excel and tools from best analytics vendors such as MicroStrategy, Tableau, Qlik, and TIBCO Jaspersoft. What’s more, the R statistical programming language can be coordinated with your company using ODBC/REST APIs.

Analytics Engines: You can offer connectors for greatly parallel processing databases for example Vertica and in addition relational database engines for example MySQL open source database and the Microsoft SQL Server, and NoSQL databases like MongoDB.

CRM and Online Marketing Solutions: You can also connect to famous CRM and online internet marketing platforms like Salesforce.com and web analytics solutions and online marketing such as Omniture and Google Analytics.