The document summarizes in-memory systems and how they enable faster and more informed decision making. It discusses how leading companies in various industries are exploring in-memory to improve decisions around staffing, dispatching, pricing and more. In-memory allows real-time processing of vast data volumes to gain insights where traditional systems took days or weeks. SAP has seen strong growth with its in-memory HANA platform. Innovation centers help users identify the right in-memory applications for their unique needs.
3. New “in-memory” systems—roughly
analogous to flash memory in small
laptops—make it much easier to
rapidly process greater volumes of
data in real time. Here’s how those
systems work, who’s behind them—
and what they promise for faster and
more informed decision making.
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4. An electrical power utility wants These leading companies’ explorations
better information about the long-term promise a myriad of economic out-
performance of its large circuit breakers comes: from better matching of staff
and their historic repair costs. A taxi with each day’s demand, in the case of
company is keen to use traffic records the retailer, to the electrical utility’s
data to improve its ability to direct and long-term cost savings over the life-
dispatch its cabs. A retail chain needs times of its circuit breakers.
better and more immediate feedback on
foot traffic and consumption patterns The quick results from some of these
in its stores so it can fine-tune its early investigations are also helping
staffing schedules. these organizations to clarify where
they can get the greatest value by being
What do these three companies have able to make better decisions more
in common? All three have hit a wall quickly. Acquiring the confidence to
when it comes to being able to act know where fast decisions about com-
on data that can, when gathered and plex scenarios can make a difference
appropriately analyzed, convey a com- to costs or competitive success, their
petitive edge. And all three—along with management teams can place their
many other businesses across a range analytics bets where they matter most.
of industry sectors—are actively explor-
ing new in-memory systems that This viewpoint paper introduces the new
promise to significantly reshape the in-memory systems, highlights their
ways in which their management benefits for business users, describes
teams make decisions. the activities of some of the leading
providers, and touches on the actions
that readers should take now.
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5. Why new approaches are Specifically, business leaders today are view of the available data is cumber-
needed now looking for faster queries against bigger some and time-consuming; with
Organizations struggle at the intersec- databases. Their organizations crave traditional divided OLTP/OLAP systems,
tion where business challenges collide real-time data, immediate and easy it can take a week to write the query
with the limits of technology. In times access, and self-service, user-centered and receive the answer.
of such enormous business volatility, systems for delivering insights. That’s
the need for rapid, confident decision why there is so much emphasis on Additionally, analytical reports typically
making is all the more acute. It is investments in analytics capabilities, do not run directly on operational data,
hardly a question of not having enough competencies and tools. but on aggregated data from a data
data; indeed, most organizations are warehouse. Operational data is trans-
unable to maximize the potential of But there is widespread frustration with ferred into this warehouse in batch jobs,
all the data they already have in their the limitations of current analytics which makes it all the more challenging
own transaction-based databases. In systems. Several business-intelligence to use flexible, ad hoc reporting on
addition, few have mastered what it barriers get in the way of effective, up-to-date data. Presentations are
takes to extract value from the data informed decision making. To begin with, made with high-level summary data
outside their own four walls—their most company data is still distributed created on spreadsheets, which do
customers’, suppliers’ and partners’ throughout a wide range of applica- not allow users to dig into accurate
databases. And even fewer know tions and stored in several disjointed information. And traditional databases
what it takes to gather and capture silos. Traditional databases rely on are still geared to structured data, which
meaningful insights from abundant half-century-old disk-drive technologies is only part of the sum of all the data
e-mails, video webcasts, blogs, and with in-built delays. Creating a unified that is useful today.
other forms of unstructured data.
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6. The arrival of in-memory in main memory, which offers perfor-
systems mance orders of magnitudes faster than
New technology developments are with traditional disk-based systems.
materializing just in time. Rapid By 2012, according to research firm
increases in silicon memory capacity Gartner, 70 percent of all Global 1000
and in the number of the processors organizations will load detailed data
per chip are producing a step change into memory as the primary method of
in the economics of data storage. Lap- optimizing the performance of their
tops that lack on-board disk drives are business-intelligence (BI) applications.
increasingly common and increasingly
attractive; Apple’s MacBook Air is one The use of in-memory technology
of the better-known examples. marks an inflection point for enter-
prise applications. With in-memory
Now so-called “in-memory” technology computing and insert-only databases
is moving into the corporate data cen- using row- and column-oriented
ter. Google searches owe at least part storage, transactional and analytical
of their speed to the diskless memory
used in the company’s giant storage
farms. It has become possible to store
data sets of whole companies entirely
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7. processing can be unified. In-memory Putting in-memory to work In-memory can rapidly process those
data warehousing finally offers the In-memory data warehousing has volumes of data; as a result, the elec-
promise of real-time computing; application in every industry sector. tricity provider could make better and
business leaders now can ask ad hoc But it is being explored with particular faster decisions about buying or selling
questions of the production transaction enthusiasm in the utilities industry, in power. And it could offer consumers
database and get the answers back telecommunications, retail and financial applications that would be able to
in seconds. services—all industries with very high trigger home appliances based on
transaction volumes and with a need the current price for electricity.
Over the past 18 months, most of the for very fast “time to insight.”
leading storage-technology vendors
have declared their involvement with In the electrical power business, for
in-memory systems. Three of the example, smart-meter technology
largest players have aggressively pur- enables remote monitoring of usage.
sued acquisitions. Hewlett-Packard But if the utility could receive and
recently purchased Vertica Systems, analyze data from an entire neighbor-
an analytic database management hood’s smart meters every 15 or 20
software company; last year, IBM minutes, it could develop a much more
bought data warehousing company valuable picture of power consumption.
Netezza while Oracle acquired Exa-
data. And SAP has developed its own
in-memory solutions in-house, launch-
ing its High Performance Analytic
Appliance (HANA) earlier this year.
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8. The electricity provider mentioned can provide clear recommendations of such vast volumes of data allows the
earlier wants to gather and interpret for action and schedule the needed taxi company to direct and dispatch
more information about its assets in work project. (See sidebar: Where cabs more efficiently and in real time.
order to make repair/replace decisions in-memory pays off.)
more quickly. The objective is to build In cases where in-memory systems’
and run complex event-processing sys- For their part, consumer packaged on-the-fly querying capabilities are
tems that generate asset alerts—for goods companies can use in-memory augmented by real-time processing, the
example, when the oil in a transformer systems to analyze their retailers‘ benefits are even more pronounced. It
is too hot or a circuit breaker fails early. point-of-sale data to predict demand can certainly make it easier for users
Among other insights, the utility is keen and activate the company’s processes to understand the value of being able
to understand what alerts it is receiv- for replenishment of stock shelves with to make decisions more quickly.
ing on other similar assets, to get a 48-hour turnaround. This can help to
sense of whether the outages are early eliminate out-of-stock scenarios during
indicators of more serious performance promotions.
issues, and to obtain a clearer picture
of how much has been spent to date And the taxi company noted earlier
on maintenance, asset by asset. relies on a technology provider that
uses SAP HANA to search through 360
The beauty of in-memory is that it million traffic records in a little over
does much more than help analyze one second. The rapid interpretation
one-time events. It enables business
users to review whole series of assets
and to do so over time. And then it
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9. Where in-memory pays off
In-memory data warehousing provides
a number of benefits to customers
including:
• Faster insight: Previously, the sheer volume of data in memory and uses a virtual layer (views)
information and computational power allowed only to access the data. In-memory is often as fast as
for pre-determined analysis of information. Data or faster than aggregated-based architectures. It
structures had to be developed to analyze the data not only retrieves data faster but also performs
and then had to be recalculated when data was calculations on the query results much faster than
updated, which took hours and diminished the fresh- disk-based architectures.
ness of information. With in-memory systems, detailed
data is loaded into memory where calculations are • Empowerment: Building aggregated and
performed “on the fly” at query time. pre-calculated data structures diminishes the
promise of self service and limits what a user
• Real-time visibility: In traditional BI systems, data can explore. In-memory provides greater
is pushed from the sources to the data warehouse. analytic flexibility because it reduces business
In-memory systems provide real-time replication users’ reliance on IT.
from ERP applications, which will provide visibility
into the real-time business insight by analyzing • Cost benefits: Memory databases can dramatically
business operations as they happen. reduce hardware and maintenance costs through
a flexible, cost-effective, real-time approach for
• Improved development time: Loading detailed data managing large data volumes. Memory provides
into memory for reporting and analysis reduces the potential cost benefits based on the amount of
need to build aggregate data structures—a key part data (memory is cheaper than data in high volumes).
of most BI deployments. IT organizations typically
must design and build a data layer optimized for
query performance. In-memory loads columns of
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10. SAP’s move Innovating on users’ terms available for use on iPads. The entire
SAP has been especially assertive with SAP has partnered with Accenture to project was completed in four weeks.
its in-memory move. The technology help users identify their most appro- In another instance, a mining conglom-
company recently made its HANA priate applications for HANA—in effect, erate is using one of the innovation
appliance software available to all enabling them to innovate on their centers to study the practicality of
customers globally, following its terms—on real-world business issues. incorporating unstructured data into
pre-launch to selected customers its decision-making processes.
in November 2010. HANA is already The two companies have set up a
making waves, giving the German network of innovation centers that Time spent at one of the centers is
software goliath its fastest-growing are designed and equipped to address an immersive experience. Visitors are
sales pipeline for new products. a wide range of challenges that orga- exposed to high-performance analytics
nizations face as they seek to glean during strategic brainstorming sessions,
In brief, HANA is a flexible, multipur- deeper insights from data, improve technology demonstrations, and day-
pose, data-source agnostic in-memory decision-making processes, and in-the-life scenarios showing analytics
appliance that combines SAP software understand the power of in-memory solutions at work in their organiza-
components optimized on hardware technology and mobility for delivering tions. Presentations on key economic,
provided and delivered by SAP's leading information anytime, anywhere. The marketplace and technology trends—
hardware partners. Data can be repli- innovation centers are effective test presentations tailored to the visitors’
cated from SAP in real time and is beds for users’ ideas: They use their situations—help them define their tech-
captured in memory as business data to rapidly develop proof-of- nology roadmaps for analytics in their
happens, where flexible views expose concept studies. industry sector and in their organiza-
analytic information rapidly. External tions. The innovation centers provide
data can be added to analytic models The centers house Accenture and SAP paths for very quickly determining time
to expand analysis across the entire specialists who work side by side and to value and for identifying the areas
organization. bring together assets from both orga- that will most resonate with users.
nizations including a fully integrated
The challenge for most users is that, SAP technology platform that drives There is no argument that in-memory
for all of its stated benefits, they are capabilities in business intelligence, data warehousing represents the next
not certain about how they can put in-memory analytics, enterprise mobil- wave of innovation in business intel-
it to work on their unique tasks. The ity, enterprise content management, and ligence. The question is about how
typical query from business users: enterprise information management. promptly companies act to take
“I want to see how it works with my advantage of what it offers.
project.” And while the concept of Recently, the innovation centers have
in-memory is easily grasped by tech- helped a leading energy-services pro- The surge of interest in SAP’s HANA
nology professionals, they struggle to vider to quickly put its spend data on is evidence enough that there is real
answer business users’ questions about mobile platforms. The center teams hunger for solutions to increasingly
how best to use this new technology utilized HANA Spend Analytics to complex business intelligence chal-
to meet business needs. extract actual spend data, loading the lenges. The technology groups at
data in the HANA system, developing leading companies already have a
a supporting data model, and building good grasp of what in-memory can
a framework of explorer views to do—and of what its weaknesses are.
quickly unlock the data and make it But if they are to persuade their busi-
ness colleagues of its merits, they
have to find low-cost, low-risk ways
to test their own company’s ideas
using in-memory tools and techniques.
Those efforts may already be overdue.
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“ 8. “Exploring New Opportunities to
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