Blog | Apr 11, 2013

Best Practices in BI: Think Big, Start Small.  Ensuring a Successful BI / Big Data Project

Kevin O'Rourke -TriCore Solutions LLCKevin ORourke

Best Practices in BI: Think Big, Start Small.  Ensuring a Successful BI / Big Data Project

Part 6 of 6: Emerging Technologies

 

What’s the Big Deal about Big Data? 

Big Data by name signifies the next generation in BI Platform capability.  The use case for big data has been around for years as organizations sought opportunities to analyze and mine non-traditional, less structured data such as weblogs, social media, email, machine sensors, photographs and video.  

Innovations in computing power and storage and decreasing costs have made it feasible to collect, store and analyze data.  Large solution vendors (IBM, SAP, Oracle, Teradata) together with industry analysts (Gartner Group, TDWI, Forrester Research) have heavily promoted the opportunities to be had with Big Data.

 

Concurrency   Kevin's Blog   Part 6

To derive real business value from big data, you need the right tools to capture and organize a wide variety of data types from different sources, and to be able to easily analyze it within the context of all your enterprise data. 

The term Big Data best describes the challenges faced with attempting to manage lots of data– moving, querying, scaling, storing and integrating very large data sets.

Big Data signifies a point when data becomes large enough that it can no longer be processed by conventional means.

 Big Data requires a high-performance platform to handle data volume, data velocity, variety and value. 

Big Data High Performance Platforms.

Infrastructure required to support big data is more complex than traditional data architecture platforms.  Each layer within the data architecture requires more sophistication to handle the non-traditional BI application requirements.  Data Acquisition must handle semi-structured and unstructured data, which is staged in NoSQL databases and distributed file systems.  Data is prepared using a multitude of tools distinct to each data source type and use case, and optimized for analysis in both traditional and non-traditional analytical environments.  Finally, specialized hardware and infrastructure platforms must be procured, administered and integrated in order to support Big Data / High Performance analytics applications.

 

 Source Data

   

Oracle and Big Data Solutions. 

Oracle is the first vendor to offer a complete and integrated solution to address the full spectrum of enterprise big data requirements. Oracle’s big data strategy is centered on the idea that you can evolve your current enterprise data architecture to incorporate big data and deliver business value, leveraging the proven reliability, flexibility and performance of your Oracle systems to address your big data requirements. 

Oracle is uniquely qualified to combine everything needed to meet the big data challenge – including software and hardware – into one engineered system. The Oracle Big Data Appliance is an engineered system that combines optimized hardware with the most comprehensive software stack featuring specialized solutions developed by Oracle to deliver a complete, easy-to-deploy solution for acquiring, organizing and loading big data into Oracle Database 11g. It is designed to deliver extreme analytics on all data types, with enterprise-class performance, availability, supportability and security. With Big Data Connectors, the solution is tightly integrated with Oracle Exadata and Oracle Database, so you can analyze all your data together with extreme performance.

 

Oracle Big Data   Kevin%27s Blog   Part 6

Conclusion

All Three Aspects of BI – People, Process and Technology, are critical for program success;

A BI Strategic Roadmap is a critical evaluation component, as it provides a rapid assessment of all aspects of BI, project portfolio management and justification;

Understand quantifiable opportunities for Cost Savings or ROI;  costs and opportunities should be known up front and evaluated throughout the entire program lifecycle;

Understand your user stories first, then evaluate technologies that best fit organizational benefits;

If your new to BI, remember Think Big, Start Small;  Develop a sound strategy, ensure a quick win;

Periodic health checks should be performed on mature BI platforms using same principles above to strategically realign the direction of the program.

Thank you for reading Part 2 of our BI Best Practices Series Think Big, Start Small.  Please refer to the links below for other Parts in the series:

We hope you enjoy other topics in the series as follows:

Part 1 of 6: Introduction

Part 2 of 6: Business Intelligence Fundamentals

Part 3 of 6: Common Data Architectures Used Within BI Platforms

Part 4 of 6: Organizational Readiness

Part 5 of 6: BI Strategy Roadmaps

Part 6 of 6: Emerging Technologies