The Top 10 Trends In Analytics 2013

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I’ve been passionate about analytics for over twenty years – but my head is still spinning with the amount of change currently going on in the analytics industry. Here’s my quick personal view of the ten top trends in Business Intelligence and Analytics for 2013 — what did I miss?

[Note that a version of this post originally appeared on the SAPPHIRE NOW area of the SAP Community Network]

1. Analytics And Business Intelligence Are Still #1

According to Gartner’s latest CIO survey, the top business priority is back to enterprise growth, and analytics and business intelligence remains the number one technology priority for 2013. And the next three technologies on the priority list (mobile, cloud, and collaboration) are all key areas for analytic innovation.

2. Increasing Analytic Maturity

Thanks to greater industry maturity and new technology opportunities, most organizations are making steps from Descriptive Analytics (“what happened?”) and Diagnostic Analytics (“why did it happen?”) towards Predictive Analytics (“what will happen”) – with Prescriptive Analytics (“how can we make it happen”) as the next frontier.

3. In-Memory is Ripping Up The Old Rules

In-memory computing is providing an opportunity to rethink information systems from scratch. According to Gartner, in-memory: “isn’t only about SAP HANA, isn’t new, isn’t unproven, isn’t only about big companies, and isn’t only about analytics”:

“In-memory computing will have a long-term disruptive impact by radically changing users’ expectations, application design principles, and vendor’s strategy”

4. Breaking Down Old Barriers

In-memory breaks down long-standing analytics barriers. For example, in-memory computing platform SAP HANA supports structured and unstructured data in a single system, and includes a sophisticated, embedded text analysis engine. Predictive or advanced analytics no longer requires a separate system – powerful analytic algorithms are available directly in-memory, without any unnecessary data movement, and thousands of times faster than disk-based predictive system. Since detailed row data is stored without any aggregation, it makes it much easier to let business people upload their own data sets to the corporate hub for analysis.

5. Operations and Analytics Are No Longer Separate

For forty years, operational systems and analytic systems have been separate because of technology limitations. That’s now changing with in-memory platforms. For example, with SAP Business Suite on HANA, transactional data is written directly to memory, where it is instantly available without any of the analytic compromises that have plagued earlier “real-time” analytics.

6. Big Data is a Big Deal

In addition to traditional “transaction data”, it’s now feasible to analyze “interaction data” (events before, after, and around a transaction, such as the products that were considered but then not purchased) and “observation data” (such as data streamed from sensors). Algorithms such as MapReduce and projects such as Hadoop have introduced new opportunities for storing and analyzing data that was previously ignored because of technology limitations. Actuaries are finding new careers and glory as “data scientists”. These new technologies have more than proved their worth in niche or standalone systems, but need to better integrated with existing corporate environments.

7. Analytics Moves To The Core

Analytics is no longer an afterthought to your transaction systems — it’s the heart of your future information infrastructure. The data you are storing now you will still have in 15 or 20 years time, while your applications may be long gone. The next generation of information infrastructures will combine big data, transactional data, analytic data and “content” into a single, coherent set of services that Gartner calls an “information capabilities framework”:

“The information capabilities framework is the people-, process- and technology-agnostic set of capabilities needed to describe, organize, integrate, share and govern an organization’s information assets in an application-independent manner in support of its enterprise information management (EIM) goals.”

SAP is working on this vision with the “real time data platform”, combining SAP HANA with Hadoop, Sybase ASE, Sybase IQ, Sybase ESP – and (crucially) end-to-end information governance.

8. Optimizing the User Experience

Today’s information consumers demand the same ease-of-use and immediate access they get in the consumer world. Business people want to be able to grab and mix information on the fly, without having to wait for it to be loaded into a corporate data warehouse. Data discovery tools such as SAP Visual Intelligence cover this essential demand – without sacrificing the corporate needs for enterprise governance (part of a “network of truth“). And of course, people expect a smooth, mobile-ready BI experience with integrated social collaboration, and the option of using a cloud-based infrastructure.

9. Information as an Asset

Along with all the technology changes, there have been big changes to analytics culture. Information is no longer a byproduct of manufacturing processes – it is fast-becoming a key part of the products themselves. Today’s retailers and service providers want to offer “customer experiences” that are tailored to individuals, optimized for the moment, and coherent over time – and that requires powerful new data platforms. As information becomes part of revenue generation, interest in information and control over budgets are swiftly moving to the business units, rather than traditional IT. This is creating new opportunities, but also new IT pressures and organizational issues.

10. The Revenge of Information Governance

As the technology gets more and more powerful, it becomes even more important to fix one of the oldest and least tractable barriers to successful BI: the pain of integrating multiple sets of quality data. Better integration between “big data,” traditional analytic systems, and transaction systems must also involve investments in data governance and solutions such as SAP Information Steward.

What did I miss? Add a comment below…

The Next Round of the Analytics Revolution

If you’d like to find out more about any of these trends, don’t hesitate to contact me, and I’ll help point you to the best experts available. If you’re interested in SAP Analytics technology, should follow the Business Intelligence areas of the SAP Community Network, subscribe to the SAP Analytics Blog, follow @sapanalytics or @timoelliott on Twitter, and join us at the analytics campus of SAPPHIRE NOW and ASUG 2013 in Orlando, May 14-16 to explore industry changes in depth, hear about companies that are implementing analytics in new way, and talk face-to-face with the experts.

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One Comment
  1. Hey Timo,

    I saw this on SAP first, but thought it would be more appropriate to comment here.

    I found this post (http://www.billchamberlin.com/30-analytics-trends-and-predictions-lists-for-2013/) very helpful in terms of trends, but it is from January, hence your post is not there, maybe shoot Bill an e-mail to get included. :-)

    Also, quick question, this recent post on insurance and BI (http://bit.ly/11HX4MP) got me thinking about how big data is helping create more efficient insurance premiums, how does the integration work with medical establishments? And if you have any links (case studies particularly) on big data & hospitals, it would be awesome.

    Thanks,

    Hristo

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