Fast analysis, better insight and rapid deployment with minimal IT involvement: these are among the benefits of in-memory analytics, but different products are appropriate for different environments. Read our in-depth report on in-memory technologies.
There was a time when the select few business intelligence users within
your organization were happy to get a weekly report. Today, smart companies
are striving to spread fact-based decision making throughout the
organization, but they know they can't do it with expensive, hard-to-use
tools that require extensive IT hand holding. The pace of business now
demands fast access to information and easy analysis; if the tools aren't fast
and easy, business intelligence will continue to have modest impact, primarily
with experts who have no alternative but to wait for an answer to a
In-memory analytics promise to deliver decision insight with the agility
that businesses demand. It's a win for business users, who gain self-service
analysis capabilities, and for IT departments, which can spend far less time
on query analysis, cube building, aggregate table design, and other time consuming
performance-tuning tasks. Some even claim that in-memory
technology eliminates the need for a data warehouse and all the cost and
complexity that entails.
There's no doubt that in-memory technology will play a big part in the
future of BI. Indeed, vendors ranging from Microsoft and MicroStrategy to
Oracle and IBM are joining the in-memory bandwagon. Yet no two products
deliver in-memory capabilities in the same way for the same business
Business users have long complained about slow query response. If managers have to wait
hours or even just a few minutes to gain insights to inform decisions, they're not likely to
adopt a BI tool, nor will front-line workers who may only have time for gut-feel decision-making.
Instead they'll leave the querying to the few BI power users, who will struggle to keep up
with demand while scarcely tapping the potential for insight. In many cases, users never ask
the real business questions and instead learn to navigate slow BI environments by reformulating
their crucial questions into smaller queries with barely acceptable performance.
Such was the case at Newell Rubbermaid, where many queries took as long as 30 minutes. An
SAP ERP and Business Warehouse user, the company recently implemented SAP's Business
Warehouse Accelerator (BWA), an appliance-based in-memory analysis application. With BWA
in place, query execution times have dropped to seconds.
"Users are more encouraged to run queries that sum up company-level data, which may entail
tens of millions of rows, yet they're not worried about killing [performance]," says Yatkwai Kee,
the company's BW administrator. Business users can now quickly and easily analyze data across
divisions and regions with queries that previously would have been too slow to execute.
Beyond the corporate world, in-memory BI tools allow state agencies and cities to stretch tax
dollars further while improving services. For example, the Austin, Texas, fire department serves
over 740,000 residents and responds to more than 200 calls a day. The department recently
deployed QlikTech's QlikView to better analyze call response times, staffing levels and financial
data. QlikTech is an in-memory analytic application vendor that has been growing rapidly in
the last few years. With QlikView, users can get to data in new ways and perform what-if analysis,
which the department says has helped in contract negotiations.
And benefits go well beyond the fire department. "Unless we spend more efficiently, costs for
safety services will take a larger share of tax dollars, making less budget available for services
such as libraries and parks," says Elizabeth Gray, a systems supervisor. Gray says that attendance
and payroll data come from different systems and never seemed to make the priority list in the
central data warehouse. "With QlikView, we can access multiple data sources, from multiple
platforms and different formats," she says. "We can control transformations and business logic in
the QlikView script and easily create a presentation layer that users love."
In many cases, in-memory products such as QlikView and IBM Cognos TM1 have been
deployed at the departmental level, because central IT has been too slow to respond to specific
business requirements. A centralized data warehouse that has to accommodate an enterprise's
diverse requirements can have a longer time-to-value. Demand for in-memory is also strong
among smaller companies that lack the resources or expertise to build a data warehouse; these
products offer an ideal alternative because they can analyze vast quantities of data in memory
and are a simpler, faster alternative to relational data marts.
A number of the tools that use in-memory approaches facilitate a more exploratory, visual
analysis. Vendors TIBCO Spotfire, Tableau Software and Advizor Solutions, for example, take
an in-memory approach that offers a stark contrast to many query and OLAP products; instead
of starting with a blank screen to build a query or a report, users start with a view of all the
data. Held in memory, this data is then filtered down to just the information users are looking
for with easy-to-use data selection, sliders, radio boxes and check boxes.
The Agile ArchiveWhen it comes to managing data, donít look at backup and archiving systems as burdens and cost centers. A well-designed archive can enhance data protection and restores, ease search and e-discovery efforts, and save money by intelligently moving data from expensive primary storage systems.
2014 Analytics, BI, and Information Management SurveyITís tried for years to simplify data analytics and business intelligence efforts. Have visual analysis tools and Hadoop and NoSQL databases helped? Respondents to our 2014 InformationWeek Analytics, Business Intelligence, and Information Management Survey have a mixed outlook.
. We've got a management crisis right now, and we've also got an engagement crisis. Could the two be linked? Tune in for the next installment of IT Life Radio, Wednesday May 20th at 3PM ET to find out.