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Big Data Analytics Tools & Technologies

What are we going to understand- <br><br>Types of Digital Data<br>What is Big data?<br>Why Big Data?<br>Big Data Analytics<br>Benefits of Big Data Analytics

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Big Data Analytics Tools & Technologies

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  1. Big DataAnalytics Tools & Technologies Department ofComputer Science & Engineering

  2. What are we going to understand Types of Digital Data What is Big data? Why Big Data? Big Data Analytics Benefits of Big Data Analytics.

  3. Types of Digital Data • Structured – Data that resides in fixed fields (data in relational databases or in spreadsheets) • Unstructured – Data that does not reside in fixed fields (untagged audio and video data, etc.) • Semi-structured – Data that does not reside in fixed fields but uses tags or other markers to capture elements of the data (XML, HTML-tagged text)

  4. Types of Digital Data • Internal – from a company’s sales, customer service, manufacturing, and employee records; from visits to the company’s website, etc. • External – from sources outside a company such as third-party data providers, public social media sites such as Facebook, Twitter and Google+, etc.

  5. What is “BIG” Data? • Volume: Enterprises are awash with ever-growing data of all types, easily amassing petabytes—even zettabytes /yottabytes—of information. • Velocity:Batch Processing—near real time—real time—streaming. • The latest heard is 10 nano seconds delay is too much. • Variety:Big data is any type of data. • Monitor 100’s of live video feeds from surveillance cameras to target points of interest

  6. Why Big-Data? • Key enablers for the appearance and growth of ‘Big-Data’ are: • Increase in storage capabilities • Increase in processing power • Availability of data

  7. Whom does it matter • Research Community . • Business Community - New tools, new capabilities, new infrastructure, new business models etc. • On sectors

  8. Big Data Analytics • Process of examining large data sets containing a variety of data types i.e., big data ,to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. • Big Data Requires High-Performance Analytics.

  9. Approach to Analytics • Reactive–business intelligence: Standard business reports, ad hoc reports, OLAP and even alerts and notifications based on analytics. • Reactive – big data BI: Reports based on BIG data. • Proactive–analytics: Making forward-looking, proactive decisions requires proactive big analytics like optimization, predictive modeling, text mining, forecasting and statistical analysis • Proactive – big data analytics : More of a culture change.

  10. Benefits of Big Data Analytics • It’s not about Data. It’s about Insight and Impact. • Enterprise can boost sales, increase efficiency, and improve operations, customer service and risk management.

  11. Aravali College of Engineering And Management Jasana, Tigoan Road, Neharpar, Faridabad, Delhi NCR Toll Free Number : 91- 8527538785 Website : www.acem.edu.in

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