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Big Data - What? Why? & How?


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Big data- it’s big, trending and the future of how world interprets and analyze. It is changing the way of how world uses raw data to transform into meaningful business information. Learn what big data has to offer along with standards and paradigms.

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Big Data - What? Why? & How?

  1. 1. Big Data What? Why? & How? Presented by KONSTANT INFOSOLUTIONS
  2. 2. What is Big Data? Big Data can be described as huge chunks of structured and unstructured data that is hard to interpret. It’s simply a mechanism to gain insights and meaningful data values from large data sets, which ultimately leads to better understanding of business progress and aids in taking better decisions.
  3. 3. History of Big Data The process of transforming raw data into meaningful information has been followed since ages. In early 2000s, a proficient analyst Doug Laney explained the growing nature of data as the three Vs, Volume, Velocity and Variety.
  4. 4.  Volume. The quantity of the data produced and stored.  Velocity. In this context, the rate at which the data is being produced and processed to meet different business challenges.  Variety. The type of the data produced. History of Big Data
  5. 5. The data has grown exponentially in the last few years making it difficult to manage and analyze, which gave birth to the term ‘Big Data’. History of Big Data
  6. 6. The Four Additional V’s While devising a Big Data strategy there are some additional parameters (some additional V’s), which require your critical eye. Here, we list the same. Veracity Variability Visualization Value
  7. 7. The Four Additional V’s  Veracity. You need to be accountable for the data being produced, stored and analyzed by the analysis team for organization’s growth, prosperity or hardship. Poor Accuracy Good Accuracy
  8. 8. The Four Additional V’s  Variability. It is the core in performing analyzes. Algorithms should be good enough to comprehend the entered data and produce meaningful insights. 0 1 2 3 4 0 0.5 1 1.5 2 2.5 3 More Variability Less Variability
  9. 9. The Four Additional V’s  Visualization. Huge chunks of complex data rendered into the simplest form with plenty of variables to work with. Not the regular graphs or pies but a graphical representation of compound data. A B C 0 2 4 6 S1 S2 S3 S4 A B C
  10. 10. The Four Additional V’s  Value. Big data churns the existing raw data sets into useful information that adds value to the business in the process of decision making and future strategy moves.
  11. 11. Importance of Big Data No matter how much data is stored inside the data banks unless it’s managed, sorted and analyzed to meaningful information. This is where Big Data comes into picture helping organizations to achieve the following,
  12. 12. Importance of Big Data The benefits come in a flurry especially when Big Data combines with analytics. Here are some of the benefits you can reap after sowing the seeds of Big Data analytics. Real-Time Bug Identification Improved Customer Analysis Effective Risk Management Reduction in Frauds
  13. 13. How It Works  Streaming Data  Social Media Channels  Publicly Available Sources The benefits come in a flurry especially when Big Data combines with analytics. Here are some of the benefits you can reap after sowing the seeds of Big Data analytics.
  14. 14. How It Works  How to store and manage it?  How much of it to analyze?  How to use any insights you uncover? Once the data sources are identified, data gets processed to yield consequential results that actually makes sense. This includes:
  15. 15. What should be your last move? Consider technologies or tools for Big Data Analytics keeping the following factors in mind:  Affordable yet effective  Massive storage capacity  Fast processors  Parallel processing, clustering, MPP, virtualization  High connectivity and high throughputs  Cloud computing  Flexible resource allocation arrangements  Popular tools like Hadoop
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