IBM sBusAnalytics LI#461099 E-Guide 092211[1]

8/3/2019 IBM sBusAnalytics LI#461099 E-Guide 092211[1]

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E-Guide

Game-changing business analytics

trends for 2011 and beyond

Business analytics technologies and techniques are constantly

evolving, as organizations look for novel ways to gain a competitive

advantage from their data and business intelligence vendors develop

new tools to help in those efforts. This E-Guide looks at new and

emerging business analytics trends and technologies that have the

potential to make winners out of the companies that adopt them and

relegate those that don‟t to the competitive sidelines.

IT and business readers will:

Learn about key developments in business analytics that areproviding new capabilities for analyzing data, including their

maturity levels and what to consider before adopting them

Read about emerging concepts, such as unstructured data analysis

and visual analysis, that have the potential to broaden the type of analytics available to end users

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Game-changing business analytics trends for 2011 and beyond

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E-Guide

Game-changing business analytics

trends for 2011 and beyond

Table of Contents

Business analytics trends yield tools with potential – if you’re ready

Data visualization, social media analytics could be keys to pervasive BI

Resources from IBM






Business analytics trends yield tools with potential– if you’re ready

By Todd Morrison, News and Features Editor

Advanced business analytics technologies such as in-memory analytics, in-database

analytics and complex event processing (CEP) tools enable organizations to analyze

increasingly massive amounts of data from a diverse number of sources, faster and more

efficiently than ever before.

But does that mean you should spend the required time and resources to implement them?

The technologies are mature enough to consider for enterprise adoption, according toindustry analysts. The biggest question may be whether your organization is ready for

them.

In fact, the first thing that any business needs to consider when thinking about buying

advanced analytics software is whether it‟s sufficiently prepared to deploy and use tools that

are more complex than mainstream business intelligence (BI) products are, said Forrester

Research Inc. analyst Boris Evelson.

“The first advice is really, „Are you ready?‟ You need to learn to walk before you can learnhow to fly,” Evelson said.

There a lot of things that have to be done – and done correctly – just to support basic BI

and analytics technologies, he noted. Data governance policies and processes need to be

put in place. Basic data management issues also have to be taken care of – for example, BI

data must be cleansed and properly integrated to ensure that key corporate information is

both accurate and accessible.

Only when those steps have been taken should an organization look at aligning itself withthe latest business analytics trends, technologies and techniques, Evelson cautioned.

“Otherwise,” he said, “it‟s like the proverb: garbage in, garbage out.”






But Evelson and other analysts said there‟s no reason to avoid emerging analytics

technologies once you‟re in a position to succeed with them. Until recently, that might not

have been the case. For example, in-memory analytics, in which queries and calculationsare run against data stored in a computer‟s memory instead of requiring information to be

pulled from disk drives, has been around for years – but it was limited by 32-bit

architectures and high memory costs. Now, thanks to 64-bit architectures and reductions in

memory prices, the technology finally appears to be hitting its stride.

As a result, all of the major BI vendors are committed to providing some kind of in-memory

analytics capabilities, if they don‟t already, according to Rick Sherman, founder of Stow,

Mass.-based consulting firm Athena IT Solutions. “It‟s a proven technology,” he said.

Business analytics trends at work: more user-friendly tools, faster performance

The increasing allure of in-memory analytics is being aided and abetted by several factors,

industry watchers said. For one thing, many business users have grown frustrated with

having to go to the IT department every time they need to create a report. At the same

time, organizations are looking for tools that are more flexible and more intuitive to use, as

part of so-called pervasive BI efforts aimed at broadening the adoption of BI and analytics

software within companies.

“We‟re seeing a trend toward technologies that are easier to use for people who aren‟t

necessarily very technical or capable of writing their own reports but still want to do their

own analysis,” said Rita Sallam, an analyst at Gartner Inc. The biggest reason in-memory

analytics has taken off, she added, is that vendors have combined the technology with user

interface tools that are highly interactive and simple to grasp.

Also working to the benefit of in-memory analytics are growing demands from business

users for faster data analysis performance, Sallam said.

Sherman agreed, saying that the amount of time it takes to do more complex analytics is a

constant source of frustration for end users. Looking at data through the lens of various

metrics “is where analytics gets slowed down considerably,” he said, while pointing to in-

memory analytics as a potential way to reduce processing times.






However, giving business users more analytical flexibility and freedom via in-memory

analytics also carries with it some risks, Evelson warned.

“It‟s a double-edged sword,” he said. “On one hand, it‟s great to empower your end users,

and it frees up the IT department. On the other hand, you start losing control. So, all of a

sudden, end users that maybe don‟t have the proper training start creating their own

reports. How do you know they‟re creating the right calculations?”

End-user training programs at organizations that are deploying in-memory analytics tools

should include sections designed to give workers a good understanding of corporate data

and data models, so they won‟t go astray in using the information and produce faulty

findings, Evelson said.

Setting the stage for scaling up advanced business analytics

In-database analytics, in which analytical processing is done directly within a data

warehouse, is also being supported by more vendors and seeing broader enterprise

adoption. Forrester analyst James Kobielus said in-database analytics tools have the

potential to help organizations scale up their data mining activities and other advanced

analytics efforts.

For example, as data mining models become increasingly complex, analytic applications

have to pull together more data, on a more continuous basis, and from a greater number of

data sources than in the past, according to Kobielus. “You need some heavy-hitting

horsepower to do that in an efficient way,” he said, adding that in-database analytics can

help speed up the process.

CEP software, which is designed to enable organizations to monitor and react to business

events in near real time, is another example of how business analytics trends are evolving.

While CEP technology typically is used to look for patterns and trends in large amounts of

financial or supply-chain data, Kobielus said new uses are emerging – for example,






monitoring Twitter and other social media networks for mentions of a company or a

product.

Kobielus described CEP, in-database analytics and in-memory analytics as “hot

technologies” that have the ability to provide significant benefits to companies ready to

handle them. “This is not bleeding edge,” he said. “This is really happening.”






Data visualization, social media analytics could bekeys to pervasive BI

By Jeff Kelly, News Editor

Business intelligence (BI) vendors and industry analysts have been talking about pervasive

BI – "BI for the masses" – for years now. But, by most accounts, BI has yet to break

through to the desktops or BlackBerrys of marketing managers, salespeople, shop floor

directors and other business users.

A recent survey of BI end users and managers by the U.K.-based Business Application

Research Center revealed that only 11% of respondents have BI deployed to more than50% of employees in their companies.

Many factors contribute to the lack of business user adoption, but an important one is the

technology itself. BI vendors are constantly touting innovations that will bring BI to the

masses, but so far to no effect.

There is hope, however. Here are three technologies that could play critical roles in

spreading BI to more business users:

Data visualization. Perhaps the most sure-fire way to spur business user adoption of BI is

to improve data visualization technology. The easier it is for non-analysts to view and make

sense of dashboards and other data visualizations, the more likely they are to use BI

technology.

A handful of vendors, both large enterprise software companies and smaller data

visualization specialists, have come up with enhancements to existing data visualization

techniques to do just that. Among them is the ability to easily overlay multiple data sets on

a bar graph or chart via drag-and-drop tools.

Other improvements include improved usability of heat maps, geographic mapping analysis

and time-series analysis charts, according to analysts.






The amount of data that data visualization tools can analyze is also on the increase, thanks

in part to in-memory technology. In-memory analytics engines load data into random

access memory rather than disk, increasing query speed and lessening the amount of datamodeling needed with traditional BI platforms.

And one open source predictive analytics language is enabling the creation of new types of

data visualizations that make previous visualizations “look kind of tacky” in comparison,

according to Marick Sinay, a financial analyst with a large multinational bank, who uses the

technology on a daily basis. Called R, the free software language was designed for statistical

computing and graphics.

Social media analytics. Social media analytics is an emerging discipline, and so are the

tools that enable it. Currently, most social media analytics technologies require significant

expertise to use and are far from perfected.

But Forrester Research Inc. analyst James Kobielus thinks that social media analytics tools –

as they become easier to use – will be integrated into traditional BI platforms. That makes it

more likely that non-power users will get their hands on the technology and understand

what the blogosphere is saying about their companies.

Facebook, the world‟s largest and most influential social networking site, is doing its part to

bring BI to the masses. The site offers page owners a number of analytics tools to monitor

and measure referral traffic, demographic data and click-through rates, according to Alex

Himel, a Facebook software engineer.

“By understanding and analyzing trends within user growth and demographics, consumption

of content, and creation of content, [Facebook] page owners and platform developers are

better equipped to improve their business with Facebook,” Himel said.

Unstructured data analysis. A related technology that could make BI more appealing to

business users is unstructured data analysis.

More than 80% of corporate data sits in Word documents, emails and other unstructured

forms, according to analysts. Much of the data business users interact with each day is






unstructured. Improving the ability to access and analyze that data would probably prompt

more business users to adopt BI technology.

Most current BI platforms are not well suited to unstructured data analysis, according to

Forrester‟s Boris Evelson. And text analytics tools have yet to reach a level of maturity that

would be inviting for non-power users.

But a couple of vendors are experimenting with integrating enterprise search technology

with more traditional BI platforms in hopes of solving both problems, Evelson said. If

successful, the new tools could prove particularly useful for marketing analytics, such as

parsing user comments and reviews from online forums.

There are other things that need to happen – including better end-user training – before BI

truly comes to the masses. But improvements in data visualization, social media analytics

and unstructured data analytics technologies would go a long way to making pervasive BI a

reality.






Resources from IBM

7 Reasons You Need Predictive Analytics Today

Decisions that Drive Success

Analytics: The New Path to Value

About IBM

At IBM, we strive to lead in the creation, development and manufacture of the industry's

most advanced information technologies, including computer systems, software, networking

systems, storage devices and microelectronics. We translate these advanced technologies

into value for our customers through our professional solutions and services businesses

worldwide.

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IBM sBusAnalytics LI#461099 E-Guide 092211[1]