Product Code: IT014-002804
Until recently, Big Data analytics have typically been associated with advanced programmatic-style analytic techniques on emerging NoSQL platforms, or complex, data mining-oriented runs against large enterprise SQL data warehouses. That triggers an obvious question -- could Hadoop become more accessible with the BI tools that have become a staple of analytics for many enterprises?
- Hadoop will augment, not replace, the traditional enterprise data warehouse.
- SQL is rapidly becoming a preferred way for BI users to access Hadoop.
- Data discovery and search tools become increasingly important as more data enters the BI process.
- Outlines new use cases for adding Hadoop to the BI stack.
- Discusses the opportunities and limitations of BI with Hadoop today and going forward.
- Discusses the types of interaction that different BI roles (casual user, power user, BI developer, BI administrator, etc) will have with Hadoop.
- When and why should Hadoop be considered for BI processes?
- How can Hadoop augment BI implementations?
Table of Contents
- Ovum view
- Key messages
- Overview of report series
- THE STATE OF BI TODAY
- Ovum's definition of business intelligence
- BI and SQL
- A mature market
- The appeal of SQL
- The limitations of SQL
- Why are we having this conversation?
- Hadoop's limitations
- Changes are on the horizon
- HADOOP ADDS BUSINESS VALUE TO BI PROCESSES
- Hadoop is not replacing EDWs...
- ...but Hadoop can go where EDWs cannot
- Keeping it raw
- Hadoop-augmented BI stack - adding new types of data sources to the BI
- Active archiving
- HOW DOES HADOOP CHANGE THE BI THOUGHT PROCESS?
- Bigger ways of answering familiar questions
- BI tools and techniques to help frame these questions
- Data discovery and search can be a first analytic step
- Search will help users find the data they are looking for
- Graph processing to better understand what is connected to what
- Who can benefit from BI on Hadoop?
- Casual end user
- Power user/data curator
- Recommendations for enterprises
- Hadoop is still a young technology - know-how might need to be acquired
- Start small and scale out
- Don't add data "just because"
- Recommendations for vendors
- Guidance and education will be key
- Expand Big Data know-how internally
- Improve Big Data-related professional services externally
- Don't run away from core BI customers
- Further reading
- Ovum Consulting