Posts Tagged ‘Forrester’

Again, this week I am gathering together a few reads that I have found to stick in my mind, for one reason or another.

The future of Analytics
The Data Warehouse Institute has a series of “Best Practice Reports”; a recent one is called Delivering Insights with Next-Generation Analytics.  It provides an analysis on the future of analysis, backed up with some survey results.  It characterises BI as central to analytics in a business context (and it’s hard to say what part of business analytics BI would not be involved in).  Reporting and monitoring remain crucial components of such activity, but TDWI places an emphasis on differentiating users of information and analytics, from production report consumers (wide in scope but terse in analytical focus) to the power user analysts and managers concerned with forecasting and modelling.  The essence of its recommendations are to provide appropriate tools to the differentiated users, and keep an eye on technology.  Although at a top level this isn’t exactly news, this report is packed with useful detail for those making an effort to keep on top of the intersection between business and technology.

The future of Data Warehouses
Although I had a look at some new technology in data warehousing recently, this second TWDI report (Next generation Data Warehouse Platforms) is necessarily more systematic.  It models the DW technology stack, outlines new technology and business drivers, intersperses user stories, and outlines emerging trends (eg appliances, in-memory, cloud/SaaS, columnar, open source, etc) not too different from my list.  Recommendations include: focusing on the business drivers; moving away from expensive in-house development; preparing for high-volume data; anticipating multiple path solutions, including open source.

In-memory databases
TDWI’s above report treated in-memory DWs seriously, without going into much detail on feasibility.  This is odd, given one of their recommendations involves preparing for an explosion in data to be stored.  I read a discussion on this technology (TDWI again: Q&A: In-memory Databases Promise Faster Results), which still doesn’t convince me that this isn’t a cat chasing its own tail.  The only realistic way forward I can see is by developing a dichotomy between core and peripheral data and functionality.  Haven’t seen that discussed.  Yet.

Forrester on trends and spotting them
Forrester has a new report aimed at Enterprise Architects: The Top 15 Technology Trends EA Should Watch.  These are grouped into five themes: “social computing for enterprises, process-centric information, restructured IT service platforms, Agile applications, and mobile as the new desktop”.  Some of it is discussed here, by Bill Ives.  Further, Forrester gives an outline of the criteria it uses for paying attention to a technology.  This includes how meaningful it is in the near term, its business impact, its game-changing potential, and its integrational complexity.

Vendor news: Oracle and bulk financials
Finally, news that Oracle has bought up again, this time taking over HyperRoll, whose software is geared for analysing “large amounts of financial data”.  Sounds a sensible move.


Read Full Post »

For my money, Gartner‘s and Forrester‘s depiction of tools has broad equivalence. Their x-axes are Completeness of Vision and Strategy respectively; their y-axes are Ability to Execute and [strength of] Current Offering. Additionally, Forrester’s Wave helpfully spells out equivalence (of a sort), and sizes out market presence.

To compare, I looked at Gartner BI Q1 2008 and Forrester Q2 08 (which periods should not exhibit marked change, to my knowledge). One should expect their analyses to have congruencies, but they do differ, sometimes significantly. The both accorded leadership to IBM [Cognos],SAP [Business Objects], Oracle [Hyperion/Siebel products], and SAS, but Gartner included Microsoft, which Forrester downgraded to second tier, along with MicroStrategy, Information Builders, and SAP Netweaver. Forrester had them rather clustered, whereas Gartner differentiated more strongly between current execution and vision, interestingly ranging them from current to future order as Microsoft, Cognos, BO, Oracle, SAS.

Gartner's BI magic quadrant, Q1 2009

Gartner's BI magic quadrant, Q1 2009

Gartner’s Q1 2009 (summary and better quality image here) has them more clustered, yet differentiated. Cognos, Oracle, and SAS are ahead, with Microsoft and SAP back. On this take, Cognos has the best current offering, while SAS has better vision. (I note here that MicroStrategy, placed in second tier tends to perform particularly well with The BI Survey [OLAP Report] on customer satisfaction, which must count for something.)

Gartner’s  observes, inter alia, a flattening of the market in terms of ROI and offering: bigger spends don’t yield greater satisfaction, and BI is becoming more accessible through open source, SaaS, and Microsoft.  But there’s a split in the market, between those going for a middleware solution (it will fit here) versus those seeking a vendor capable of providing a fully integrated product set – which puts a context on those market consolidations.

The overall impression I get is that one cannot guarantee a clear leader as the manufacturers attempt to leapfrog each other with each new release. It’s also worth mentioning the change in the BI market over the past five years or so, from straightforward query/analysis/report to a plethora of tools (dashboards, scorecards, etc) for conveying that intelligence to the right people.

Of other interest for BI is: database, data integration, data quality, and collaboration tools.

In Data Warehousing, current analysis has few surprises. Forrester puts Teradata, IBM, and Oracle at the forefront, with Teradata slightly ahead due to strength of current offering. Standing back is Microsoft, still depicted as a leader due to their strategy more than their current offering. Which takes us to collaborative tools, which goes some of the way to explaining Microsoft’s strength, particularly due to their Sharepoint products. This week, someone from a Microsoft-focused shop told me he was not selling on the basis of SQL Server products so much as Sharepoint – because of its presentation presence, albeit it being back-ended by SQL Server (an analysis can be read with the graph here at Intelligent Enterprise).

Data quality tools? Gartner’s has rather changed in the past six months, now putting Dataflux clearly ahead, with Informatica and IBM [DataStage] bunched behind (viewed here).

Data Integration? As of Sept-08, IBM/DataStage were at front, with SAP/BO trailing, followed by SAS, with Microsoft and Oracle surrpisingly far back in the field, due both to current offering and vision. Simple picture here.

Gartner’s BI-specific page has a lot of information to absorb; Forrester’s page is mostly just links to reports.

Accompanying analyses are intrinsic, but as Get Elastic points out, there’s no “one size fits all”.  You have to assess on their ability to meet business needs; on the basis of choosing leadership alone can burn fingers.

My experience is that every tool has its pain points, in terms of both capability and usability. The quality of implementation is probably a bigger determinant of success than toolset (amongst the general leaders, at least; niche players such as Qlikview do not have the broad capabilities called for in a comprehensive tool). Like data mining, successful implementation is more likely with experienced implementers – that is, consultants. Yet there are traps there, too. I’ve seen consultant installs that have shown insufficient business insight, and/or have left behind insufficient documentation or transferrence of skills – either of which can deflate an initiative.

Moreover, it has to be accepted that BI is an ongoing project. If a consultant sets and an enterprise forgets, a couple of years down the track there will be significant atrophy of relevance. Business needs, expectations, and technological possibilities are constantly evolving. That latter is where product leadership has the most significance.

Read Full Post »