Recently in Cloud Category

Each year I form my opinion based on the observations from five sources; our customers, industry conferences, articles, social media and BI software vendors.  2010 proved to be an interesting year on many fronts.  My observations from 2010 are as follows:

1)  Larger numbers of existing BI programs are maturing beyond managed reports, ad-hoc queries, dashboards and OLAP than in years past.  Companies are increasingly looking to squeeze more value out of their BI programs via advanced visualization, predictive analytics, spatial analysis, operational BI and collaboration.  This is driving the rise of analytic databases (ADB's) and new analytic applications and features.

2)  The number of failed BI projects continues to remain high.  While the industry has learned, and documented, the reasons of why projects fail, it hasn't done much to stem the tide of failed projects.  From my perspective, and I'm sure most would concur, the overarching reason is because implementing successful BI projects is hard.  It requires a balance of strong business involvement, thorough data analysis, scalable system & data architectures, comprehensive program and data governance, high quality data, established standards & processes, excellent communication & project management and, experience.  I don't necessarily see things changing in 2011 unless companies:

• institute and enforce Enterprise data management practices

• ensure high levels of business involvement for BI projects

• institute measurable, value driven, metrics for each BI project

• realize that offshoring BI projects, except for simple staging ETL and simple BI reports, doesn't work well for BI.
  

3)  Much of the old is new again.  Master Data Management (MDM), dashboarding and predictive analytics are not new concepts, but they did see a strong reemergence in 2010.  One of the challenges with implementing integrated dashboards and predictive analytics was that they were often missing from the enterprise BI software suites.  It seems that the major BI vendors finally started listening to their customers are new capabilities started rolling out.  MDM was simply repackaged to include more than just the data warehouse and found traction in organizations struggling with defining their master data and keeping it consistent across their disparate systems.

4)  BI wants to be agile. We've always recognized the high cost and long lead times for implementing BI, but it seems that the customer has finally said 'enough' and BI teams are listening.  They are looking for new ways to implement BI and finding that many Agile practices, such as smaller, focused iterations, daily scrum meetings, prototyping and integrated testing help speed up the velocity of BI and augment the communication between the business and IT. In 2011, I expect to see BI practitioners better understand what Agile practices work with BI and which one's don't translate as well.

5)  There was increasing interest in BI in the Cloud, but fewer takers than expected.  Infrastructure as a service is still a bit too technical for many BI programs to implement and concerns over data security remain high.  There are also concerns over performance, both hardware and network.  BI software as a service products are continuing to mature but  the biggest hindrance for user adoption in 2010 appeared to be poor ETL capabilities and non-extensible identity & access management.    

I'm always interested in you reaction and views.  Please feel free to post your comments and take on 2010.  

When you mention BI in the Cloud amongst database vendors and BI practitioners, chances are you'll land on the topic of performance within the first minute or two of the conversation.  Until recently, there was little to debate as limited image sizes, slow storage and shared networks limited the performance of Hardware-as-a-Service (HaaS) based solutions. However, recently Amazon announced the availability of Cluster Compute Instances for Amazon's Elastic Computing Cloud (EC2).  Cluster Compute Instances provide more CPU than any other Amazon EC2 instance. Customers can also group Cluster Compute Instances into clusters allowing applications to get the low-latency network performance required for tightly coupled, node-to-node communication (typical of many BI architectures). Cluster Compute Instances also provide significantly increased network throughput making them well suited for customer applications that need to perform network-intensive operations.

It won't be long before purpose built Clouds start to hit the market, designed specifically to meet the high compute and i/o demands of BI.  Kognitio is already providing a SaaS based solution for hosted data warehouses and front-end BI applications.  From my standpoint, it won't be long before performance will drop off the list of top BI in the Cloud concerns and BI practitioners will wonder why they ever implemented and managed onsite BI architectures.