Despite Silly Misconceptions, Big Data Brings New Hope for Better Decision-Making

Big Data is a silly term, overhyped and misunderstood. Big Data is often thought to equal Hadoop, especially among those who think that Hadoop is a product for solving Big Data problems. That is incorrect as Hadoop is actually a family of Apache open source projects for managing and analyzing data of all types. In fact, Big Data is a concept that has become a movement to once again treat data with probability theory and computational statistics. But for all the misconceptions surrounding Big Data, 11 innovative trends are occurring due to this movement:

  1. Improving signal-to-noise ratio when using data to make decisions
  2. Visualization and storytelling bringing data to life
  3. Reducing implementation complexity
  4. Providing confidence in decisions
  5. Introducing novel data stores
  6. Addressing new data types
  7. Exploring new business scenarios
  8. Responding to new technologies
  9. Governing the data for acceptance
  10. Integrating the Cloud
  11. Increasing the reach of data-driven decisions

These innovations allow for a Big Data and Data Science architecture that supplements, without replacing, existing Information Technology (IT) systems.

Of course, interweaving the volumetric flows of diverse and complex data types presents new challenges and opportunities in Data Management and Analytics (DMA). These challenges allow us to explore four ways of using data to inform our instincts in making better decisions and even automating decision-making:

  1. Inference
  2. Prediction
  3. Insight
  4. Performance

To be sure, vendors, open source communities, data science teams and end users are starting to bring the results of these innovations into government organizations, businesses of all sizes and even personal lives. In the end, there’s hope emerging from the Big Data hype.

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