In-Memory-Path to Better Decisions Using AnalyticsOV

7/31/2019 In-Memory-Path to Better Decisions Using AnalyticsOV

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Title of brochure

In-memoryThe Path to Making Better

Decisions More Quickly


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New in-memory systemsroughlyanalogous to flash memory in small

laptopsmake it much easier to

rapidly process greater volumes of

data in real time. Heres how those

systems work, whos behind them

and what they promise for faster and

more informed decision making.


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An electrical power utility wants

better information about the long-term

performance of its large circuit breakers

and their historic repair costs. A taxi

company is keen to use traffic records

data to improve its ability to direct and

dispatch its cabs. A retail chain needs

better and more immediate feedback on

foot traffic and consumption patterns

in its stores so it can fine-tune its

staffing schedules.

What do these three companies havein common? All three have hit a wall

when it comes to being able to act

on data that can, when gathered and

appropriately analyzed, convey a com-

petitive edge. And all threealong with

many other businesses across a range

of industry sectorsare actively explor-

ing new in-memory systems that

promise to significantly reshape the

ways in which their management

teams make decisions.

These leading companies explorations

promise a myriad of economic out-

comes: from better matching of staff

with each days demand, in the case of

the retailer, to the electrical utilitys

long-term cost savings over the life-

times of its circuit breakers.

The quick results from some of these

early investigations are also helping

these organizations to clarify where

they can get the greatest value by being

able to make better decisions morequickly. Acquiring the confidence to

know where fast decisions about com-

plex scenarios can make a difference

to costs or competitive success, their

management teams can place their

analytics bets where they matter most.

This viewpoint paper introduces the new

in-memory systems, highlights their

benefits for business users, describes

the activities of some of the leading

providers, and touches on the actions

that readers should take now.


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Why new approaches areneeded nowOrganizations struggle at the intersec-

tion where business challenges collide

with the limits of technology. In times

of such enormous business volatility,

the need for rapid, confident decision

making is all the more acute. It is

hardly a question of not having enough

data; indeed, most organizations are

unable to maximize the potential of

all the data they already have in their

own transaction-based databases. Inaddition, few have mastered what it

takes to extract value from the data

outside their own four wallstheir

customers, suppliers and partners

databases. And even fewer know

what it takes to gather and capture

meaningful insights from abundant

e-mails, video webcasts, blogs, and

other forms of unstructured data.

Specifically, business leaders today are

looking for faster queries against bigger

databases. Their organizations crave

real-time data, immediate and easy

access, and self-service, user-centered

systems for delivering insights. Thats

why there is so much emphasis on

investments in analytics capabilities,

competencies and tools.

But there is widespread frustration with

the limitations of current analytics

systems. Several business-intelligencebarriers get in the way of effective,

informed decision making. To begin with,

most company data is still distributed

throughout a wide range of applica-

tions and stored in several disjointed

silos. Traditional databases rely on

half-century-old disk-drive technologies

with in-built delays. Creating a unified

view of the available data is cumber-

some and time-consuming; with

traditional divided OLTP/OLAP systems,

it can take a week to write the query

and receive the answer.

Additionally, analytical reports typically

do not run directly on operational data,

but on aggregated data from a data

warehouse. Operational data is trans-

ferred into this warehouse in batch jobs,

which makes it all the more challenging

to use flexible, ad hoc reporting onup-to-date data. Presentations are

made with high-level summary data

created on spreadsheets, which do

not allow users to dig into accurate

information. And traditional databases

are still geared to structured data, which

is only part of the sum of all the data

that is useful today.


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The arrival of in-memorysystemsNew technology developments are

materializing just in time. Rapid

increases in silicon memory capacity

and in the number of the processors

per chip are producing a step change

in the economics of data storage. Lap-

tops that lack on-board disk drives are

increasingly common and increasingly

attractive; Apples MacBook Air is one

of the better-known examples.

Now so-called in-memory technology

is moving into the corporate data cen-

ter. Google searches owe at least part

of their speed to the diskless memory

used in the companys giant storage

farms. It has become possible to store

data sets of whole companies entirely

in main memory, which offers perfor-

mance orders of magnitudes faster than

with traditional disk-based systems.

By 2012, according to research firm

Gartner, 70 percent of all Global 1000

organizations will load detailed data

into memory as the primary method of

optimizing the performance of their

business-intelligence (BI) applications.

The use of in-memory technology

marks an inflection point for enter-

prise applications. With in-memorycomputing and insert-only databases

using row- and column-oriented

storage, transactional and analytical

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processing can be unified. In-memory

data warehousing finally offers the

promise of real-time computing;

business leaders now can ask ad hoc

questions of the production transaction

database and get the answers back

in seconds.

Over the past 18 months, most of the

leading storage-technology vendors

have declared their involvement with

in-memory systems. Three of the

largest players have aggressively pur-sued acquisitions. Hewlett-Packard

recently purchased Vertica Systems,

an analytic database management

software company; last year, IBM

bought data warehousing company

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.

Putting in-memory to workIn-memory data warehousing has

application in every industry sector.

But it is being explored with particular

enthusiasm in the utilities industry, in

telecommunications, retail and financial

servicesall industries with very high

transaction volumes and with a need

for very fast time to insight.

In the electrical power business, for

example, smart-meter technology

enables remote monitoring of usage.But if the utility could receive and

analyze data from an entire neighbor-

hoods smart meters every 15 or 20

minutes, it could develop a much more

valuable picture of power consumption.

In-memory can rapidly process those

volumes of data; as a result, the elec-

tricity provider could make better and

faster decisions about buying or selling

power. And it could offer consumers

applications that would be able to

trigger home appliances based on

the current price for electricity.

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The electricity provider mentioned

earlier wants to gather and interpret

more information about its assets in

order to make repair/replace decisions

more quickly. The objective is to build

and run complex event-processing sys-

tems that generate asset alertsfor

example, when the oil in a transformer

is too hot or a circuit breaker fails early.

Among other insights, the utility is keen

to understand what alerts it is receiv-

ing on other similar assets, to get a

sense of whether the outages are earlyindicators of more serious performance

issues, and to obtain a clearer picture

of how much has been spent to date

on maintenance, asset by asset.

The beauty of in-memory is that it

does much more than help analyze

one-time events. It enables business

users to review whole series of assets

and to do so over time. And then it

can provide clear recommendations

for action and schedule the needed

work project. (See sidebar: Where

in-memory pays off.)

For their part, consumer packaged

goods companies can use in-memory

systems to analyze their retailers

point-of-sale data to predict demand

and activate the companys processes

for replenishment of stock shelves with

48-hour turnaround. This can help to

eliminate out-of-stock scenarios duringpromotions.

And the taxi company noted earlier

relies on a technology provider that

uses SAP HANA to search through 360

million traffic records in a little over

one second. The rapid interpretation

of such vast volumes of data allows the

taxi company to direct and dispatch

cabs more efficiently and in real time.

In cases where in-memory systems

on-the-fly querying capabilities are

augmented by real-time processing, the

benefits are even more pronounced. It

can certainly make it easier for users

to understand the value of being able

to make decisions more quickly.


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Faster insight: Previously, the sheer volume of

information and computational power allowed only

for pre-determined analysis of information. Data

structures had to be developed to analyze the data

and then had to be recalculated when data was

updated, which took hours and diminished the fresh-

ness of information. With in-memory systems, detaileddata is loaded into memory where calculations are

performed on the fly at query time.

Real-time visibility: In traditional BI systems, data

is pushed from the sources to the data warehouse.

In-memory systems provide real-time replication

from ERP applications, which will provide visibility

into the real-time business insight by analyzing

business operations as they happen.

Improved development time: Loading detailed data

into memory for reporting and analysis reduces the

need to build aggregate data structuresa key part

of most BI deployments. IT organizations typically

must design and build a data layer optimized for

query performance. In-memory loads columns of

data in memory and uses a virtual layer (views)

to access the data. In-memory is often as fast as

or faster than aggregated-based architectures. It

not only retrieves data faster but also performs

calculations on the query results much faster than

disk-based architectures.

Empowerment: Building aggregated and

pre-calculated data structures diminishes the

promise of self service and limits what a user

can explore. In-memory provides greater

analytic flexibility because it reduces business

users reliance on IT.

Cost benefits: Memory databases can dramatically

reduce hardware and maintenance costs througha flexible, cost-effective, real-time approach for

managing large data volumes. Memory provides

potential cost benefits based on the amount of

data (memory is cheaper than data in high volumes).

Where in-memory pays off

In-memory data warehousing providesa number of benefits to customersincluding:


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SAPs moveSAP has been especially assertive with

its in-memory move. The technology

company recently made its HANA

appliance software available to all

customers globally, following its

pre-launch to selected customers

in November 2010. HANA is already

making waves, giving the German

software goliath its fastest-growing

sales pipeline for new products.

In brief, HANA is a flexible, multipur-

pose, data-source agnostic in-memory

appliance that combines SAP software

components optimized on hardware

provided and delivered by SAP's leading

hardware partners. Data can be repli-

cated from SAP in real time and iscaptured in memory as business

happens, where flexible views expose

analytic information rapidly. External

data can be added to analytic models

to expand analysis across the entire

organization.

The challenge for most users is that,

for all of its stated benefits, they are

not certain about how they can put

it to work on their unique tasks. The

typical query from business users:

I want to see how it works with my

project. And while the concept of

in-memory is easily grasped by tech-

nology professionals, they struggle to

answer business users questions about

how best to use this new technology

to meet business needs.

Innovating on users termsSAP has partnered with Accenture to

help users identify their most appro-

priate applications for HANAin effect,

enabling them to innovate on their

termson real-world business issues.

The two companies have set up a

network of innovation centers that

are designed and equipped to address

a wide range of challenges that orga-

nizations face as they seek to glean

deeper insights from data, improve

decision-making processes, and

understand the power of in-memory

technology and mobility for delivering

information anytime, anywhere. The

innovation centers are effective test

beds for users ideas: They use theirdata to rapidly develop proof-of-

concept studies.

The centers house Accenture and SAP

specialists who work side by side and

bring together assets from both orga-

nizations including a fully integrated

SAP technology platform that drives

capabilities in business intelligence,

in-memory analytics, enterprise mobil-

ity, enterprise content management, and

enterprise information management.

Recently, the innovation centers have

helped a leading energy-services pro-

vider to quickly put its spend data on

mobile platforms. The center teams

utilized HANA Spend Analytics to

extract actual spend data, loading the

data in the HANA system, developing

a supporting data model, and building

a framework of explorer views to

quickly unlock the data and make it

available for use on iPads. The entire

project was completed in four weeks.

In another instance, a mining conglom-

erate is using one of the innovation

centers to study the practicality of

incorporating unstructured data into

its decision-making processes.

Time spent at one of the centers is

an immersive experience. Visitors are

exposed to high-performance analytics

during strategic brainstorming sessions,

technology demonstrations, and day-

in-the-life scenarios showing analytics

solutions at work in their organiza-

tions. Presentations on key economic,

marketplace and technology trends

presentations tailored to the visitors

situationshelp them define their tech-nology roadmaps for analytics in their

industry sector and in their organiza-

tions. The innovation centers provide

paths for very quickly determining time

to value and for identifying the areas

that will most resonate with users.

There is no argument that in-memory

data warehousing represents the next

wave of innovation in business intel-

ligence. The question is about how

promptly companies act to take

advantage of what it offers.

The surge of interest in SAPs HANA

is evidence enough that there is real

hunger for solutions to increasingly

complex business intelligence chal-

lenges. The technology groups at

leading companies already have a

good grasp of what in-memory can

doand of what its weaknesses are.

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 companys ideas

using in-memory tools and techniques.

Those efforts may already be overdue.


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Sources1. In-Memory Data Management:

An Inflection Point for Enterprise

Applications, Hasso Plattner and

Alexander Zeier, Springer-Verlag

Berlin Heidelberg 2011, ISBN 978-

3-642-19362-0 e-ISBN 978-3-

642-19363-7

2. Benefits of in-memory computing,

Financial Times, June 1, 2011,

www.ft.com/cms/s/0/ee237d7a-

8c6e-11e0-883f-00144feab49a

.html#ixzz1Y4LWC300

3. Accenture and SAP Announce

Strategic Relationship to Develop

and Deploy New Mobility Solutions,

Accenture press release, May 17, 2011,

http://newsroom.accenture.com/

article_display.cfm?article_id=5203

4. Accenture Recognized as a Leader

in IDC MarketScape Cited for SAP

Implementation Skills, Accenture

press release, June 23, 2010, http://

newsroom.accenture.com/article_

display.cfm?article_id=5020

5. Invent new possibilities with

the SAP HANA Appliance, SAP

website, www.sap.com/hana/

overview/index.epx

6. Understand the Power of SAP

In-Memory Computing: Virtual

Event Webcast, SAP website,

www.sap.com/hana/asset/index

.epx?id=bd9d7124-fc5f-4937-

82b9-95d594194838

7. Accenture Technology Vision

2011The Technology Waves That

Are Reshaping the Business Land-scape, Accenture, 2011, www.

accenture.com/us-en/technology/

technology-labs/Pages/insight-

accenture-technology-vision-

2011.aspx

8. Exploring New Opportunities to

Unlock the Value of Data, Accenture,

2008, www.accenture.com/us-en/

Pages/service-sap-master-data-

management.aspx

9. SAP HANA Now Generally Available

to Customers Worldwide, SAP

press release, June 21, 2011

www.sap.com/hana/news.epx?

articleID=17213&Category=

550&class=byd-news-overlay

10. BI Applications Benefit From

In-Memory Technology Improve-

ments, Gartner Research Note

G00141540, Kurt Schlegel, Mark

A. Beyer, Andreas Bitterer, Bill

Hostmann, October 2, 2006.


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Copyright 2011 Accenture

All rights reserved.

Accenture, its logo, and

High Performance Delivered

are trademarks of Accenture.

About AccentureAccenture is a global management

consulting, technology services and

outsourcing company, with more than

223,000 people serving clients in

more than 120 countries. Combining

unparalleled experience, comprehen-

sive capabilities across all industries

and business functions, and extensive

research on the worlds most success-

ful companies, Accenture collaborates

with clients to help them become

high-performance businesses and

governments. The company generated

net revenues of US $21.6 billion for

the fiscal year ended August 31, 2010.

Its home page is www.accenture.com.

About the authorsHettie Tabor is a seasoned Accenture

senior executive based in Accentures

Dallas office. She has more than 23

years of IT experience, including 17

years of practical SAP implementation

experience. Ms. Tabor currently leads

Accentures SAP Business Analytics

Global Group and has a wealth of

technical and project management

knowledge about SAP Business

Intelligence, HANA, BusinessObjects,

Business Planning and Consolidation,

and Data Management.

Nicola Morini Bianzino leads the Global

Accenture Analytics Innovation Center

Network. Joining Accenture in 1998, Mr.

Bianzino has been working in the ana-lytics and ERP space since the beginning

of his career at Accenture, focusing

on major global implementations. He

is based in San Jose, California.

For further information about

in-memory systems, please contact:

Hettie Tabor

SAP Business Analytics Global Lead

[email protected]

Nicola Morini Bianzino

Accenture Analytics Innovation

Center Global Lead

[email protected]

Documents

In-Memory-Path to Better Decisions Using AnalyticsOV