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Fitting OLAP Into BI

by Lyndsay Wise, President, WiseAnalyticsTuesday, May 25, 2010

Within traditional BI deployments, online analytical processing (OLAP) has always been the analytics tool of choice.  With reports being delivered to general BI consumers, OLAP is considered a tool relegated to super users trying to identify trends and gain deeper insights into large data sets.  Until recently, only advanced BI users have been able to tap into the true benefits of OLAP due to its complexity.  With the maturity of BI use, diversity of available solutions, and the general push towards consumer-facing applications, business users now have the ability to apply OLAP to their BI repertoire.

With BI applications expanding to address the needs of non-technical business users, the types of analytics available to everyone within the organization is expanding.  This leads to more ROI and the ability to better align strategic goals with overall business performance.  The reason behind this is that when more people within the organization have access to a broader set of information easily - and when they can ask and answer questions interactively without the frustration of having to run to a third party to have analytics developed or accessed for them - not only do these employees feel more empowered within their company role, but they are also able to delve deeper and become more adept at what is happening within the company.  This in turn leads to better decision-making and more efficient use of time.

To gain these benefits, organizations first have to understand the role of OLAP within a broader business intelligence framework.  Second, businesses should be able to communicate the benefits they get out of BI.  And finally, companies require OLAP tools that can be broadly applied within organizations, within dashboards and help generate collaboration.  The following sections offer a closer look of these themes.

The role of OLAP within BI

OLAP plays a key role within business intelligence and analytics.  With OLAP, organizations can perform multidimensional analyses to look at information over time or to integrate disparate data sources to create a cohesive view of the organization.  Even though some companies do not require this type of in-depth insight on a regular basis, most businesses using BI are attracted to using some level of advanced analytics, whether for predictive modeling, risk identification or projecting performance based on past trends.

Overall, OLAP provides that deep dive that is required to drive performance to the next level.  The ability to look at data in multiple ways and to gain broader insights directly leads to better performance management because this added visibility gives companies information that was inaccessible.  Without the proper data, people don’t even know what questions to ask.  Once valuable information and the ability to manipulate it exist, gaps can be identified, leading to a larger understanding of what is happening within the organization.  Although general BI uses also enable broader data visibility and deeper insights into performance, OLAP goes the extra step to help those who want to think out of the box.

BI to gain general insights

Obviously, BI use and OLAP are intertwined and deeply linked.  Where BI reporting and dashboarding provides the initial glimpse into daily performance, OLAP looks at the wider picture at a micro level.  The ability to combine both gives companies the best of both worlds.  Although this seems intuitive, the reality is that many organizations cannot explain the value BI will bring to the company, and others are unable to decipher the actual ROI being achieved through BI use.  Consequently, selling the benefits of BI to the larger organization when big monetary investments are involved can be difficult.  After all, reports do provide a regular or static view of operations, with drill-through capabilities leading to broader information attainment. 

To really sell the benefits of OLAP and BI in general, companies need to identify what they hope to achieve through BI use.  This means looking beyond the general “sell” concepts such as reduce costs, increase efficiencies, etc. and start identifying specific actionable goals, such as gaining visibility into customers to lower churn by x%, or to understand discrepancies in product sales by sales rep. or by region, etc.  Once realistic goals are set that are tailored towards the strategic goals of the business, the value proposition of OLAP increases because of the visibility it provides into the business pains being faced, leading towards BI as the impetus to solving current business issues.

Best-of-breed OLAP use

Beyond vast OLAP usage within BI, analytics companies and BI solutions offer strong OLAP capabilities for analysts requiring more information than general BI provides.  In addition, with the push towards business-facing applications, the ability to interact with technology (and analytics in particular) pushes the gap of BI as a super-user tool towards being accessible by all decision makers within the organization.  Whether through interactive dashboards that integrate OLAP functionality or through traditional BI solutions with enhanced drag-and-drop environments and guided wizards, OLAP is becoming a realistic part of any employee’s BI experience.

Recommendations

Selecting a BI solution is no easy task.  With the plethora of solutions offered, it can be difficult to identify the key differentiators of any one solution over another.  The addition of best-of-breed functionality, such as OLAP requirements, can add to the general confusion.  The benefit of looking at OLAP however, is the fact that many BI solutions developed their platforms based on strong OLAP capabilities and have continued to focus on analytics as the basis of their product expansion.  Also, the move towards customer-facing applications transforms BI analytics into a tool that is readily accessible by all.

For organizations looking for these solutions for the first time, it becomes important to consider:

  • The general purpose of analytics and how it ties into the framework and overall business goals of the organization.
  • Ease of use and who will be using it – depending on which employees will be interacting with the OLAP portion of BI may affect the solution choice as those requiring in-depth statistical, risk or predictive analytics have different analytics needs than sales and marketing analysts.
  • Current BI needs versus planned projects and overall expansion.
  • General maintenance and the ability to accommodate slowly changing dimensions as business requirements and the type of analytics change.

About the Author

Lyndsay Wise is an industry analyst for business intelligence. For over seven years, she has assisted clients in business systems analysis, software selection and implementation of enterprise applications. Lyndsay is the channel expert for BI for the Mid-Market at B-eye-Network and conducts research of leading technologies, products and vendors in business intelligence, marketing performance management, master data management, and unstructured data. She can be reached at lwise@wiseanalytics.com. And please visit Lyndsay's blog at myblog.wiseanalytics.com.


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