The big machine: creating value out of machine-driven big data

Table of Contents

  1. Summary
  2. Audience
  3. About Dave Ohara
  4. Big data, big opportunity
  5. What is big data?
    1. The structure and scale of big data
    2. Data as a byproduct of operations
    3. Understanding machine data
  6. Your data tells a story
    1. Approaches
  7. Considerations
    1. Give priority to the business case
    2. Plan for access control
    3. Plan for scalability
    4. Develop a strategy for data retention
    5. Include a statistical aggregation capability
    6. Empower users with an accessible interface
    7. Provide for advanced analysis scenarios
    8. Ensure that queries are responsive
    9. Provide a dynamic environment
    10. Choose cloud or on-premises
    11. Make data cleaning and management a priority
    12. Provide for a heterogeneous environment
    13. Consider combining data sources
    14. Include configuration data
    15. Provide for queries that include time intervals
  8. Trends and Opportunities
    1. Rising expectations
    2. Demands for self-service
    3. Vertical solutions
  9. Key Takeaways
  10. Further reading and resources

1. Summary

Big data continues to offer more and more opportunity for businesses. By analyzing the information already in an organization, executives can save cost and increase revenue. For example, you may discover that you need to stock certain items in your inventory at particular times, or you may be able to offer customers incentives in real time to buy more of your products. Companies can now take advantage of data that has traditionally been overlooked because of the falling cost of computing and the evolution of new technologies that help analyze large amounts of information. This information is mostly created by machines as a byproduct of normal operations. Examples of operational data include call detail records and event logs. This paper explains how business executives working with their CTOs or CIOs and other tech management can use big data within their organizations. It explains what big data is and how it differs from traditional business intelligence. The different considerations executives should take into account as they plan their big data strategies are discussed. For example, is it better to build your own system or to buy one? Should you run your system on premises or in the cloud? How do you plan for access control and scalability? The paper also includes examples of how some companies are putting their operational data to creative use. Remember that users are becoming accustomed to faster response times and to richer data sources. They also expect self-service access to resources. Big data can help you to satisfy all of these requirements. If your organization doesn’t have a strategy for big data now, you will need one in the future.

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