how to gain control over big data projects - sba

8/20/2019 How to Gain Control Over Big Data Projects - SBA

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E-Guide

HOW TO GAIN

CONTROL OVER

BIG DATA

PROJECTS

▲



P A G E 2 O F 9 S P O N S O R E D B Y

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Businesses doubledown on big datavalue, analytics ROI

Big data growthincreases dataintegration degree ofdifficulty

HOW TO GAIN CONTROL OVER BIG DATA PROJECTS

OW THAT YOU have your analytics projects

in place, how can you ensure your organi-

zation gains true business value fromthese initiatives? In this e-guide, learn

why industry leaders are focusing on big data value and maturity

models. Additionally, uncover the data integration challenges orga-

nizations are faced with given the boom in big data growth.

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BUSINESSES DOUBLE DOWN ON BIG DATA VALUE,ANALYTICS ROI

Ed Bu rns, Site Editor

Businesses increasingly are done with academic and proof-of-concept analyt-

ics projects and are doubling down on extracting real business value from their

data. The notion that more companies are now looking for tangible returns on

their analytics investments was supported by two announcements over the

past month: the release of survey results by IBM showing a heightened focus on

big data value, and TDWI's launch of an online tool for assessing the maturity

of analytics programs.

IBM SAYS BUSINESSES HAVE A NEED FOR ANALYTICS SPEED

In a survey of more than 1,000 businesses, IBM found that 63% of the organiza-

tions that had implemented big data technology saw an ROI within one year,

which is up 10 percentage points compared to the results of a similar survey

last year. And nearly three-quarters of the respondents said they expect their

business executives to demand faster data-driven insights in the year ahead,




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according to a report on the survey that IBM issued last week.Report co-author Glenn Finch, global leader for technology and data in

IBM's Global Business Services unit, said those the increasing ROI and greater

demand for speed reflect a change in how businesses look at big data analytics.

He feels that 2014 has been a "breakout year," in which big data projects went

from theoretical to value-focused. And now that businesses increasingly are

focused on big data value, they want to speed up their analytics processes to

help differentiate from the competition, according to Finch.

"Between the speed and what they're doing, it's a pretty big shift," he said.

"Last year, everyone was talking about what they were going to do. This year,

they started doing it."

One of the main changes in this year's survey results from previous years

is that businesses are now more likely to use their analytics programs to try to

improve operational efficiency. In the past, the survey showed that analytics

applications were being applied primarily to customer issues, like service or

the acquisition of new customers. But 40% of the 2014 respondents said they're

using analytics to boost efficiency, up 15 percentage points over last year.




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TDWI RELEASES ITS ANALYTICS MATURITY MODELTDWI -- formally known as The Data Warehousing Institute -- last week issued

the Analytics Maturity Model, an online self-assessment tool that the research

and education group said would help businesses focus their burgeoning analyt-

ics projects on the importance of value.

TDWI previously developed business intelligence and big data maturity

models, which allow businesses to assess the progress of their projects and

compare them to initiatives at other organizations. The new maturity model

is the first created by TDWI to focus exclusively on analytics.

The model charts an organization's progress from evaluating software

and implementing simple tools to developing a data-driven culture, getting

executive buy-in and operating well-established projects with strong data

governance.

In a press release, Fern Halper, TDWI's research director for advanced ana-

lytics, said the goal of the new model is to help businesses understand where

their analytics projects stand and see where they have to improve in order to

start getting real business value out of their data. Users who complete the 35

questions that are part of the assessment will receive a score assessing the cur-

rent status of their analytics efforts.




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CORTANA SCORES AT PREDICTING NFL GAMESMicrosoft's voice-activated mobile device assistant, Cortana, has quietly been

racking up a strong record for correctly predicting the winners of NFL games.

So far, it has a record of 108-55 on picks this season.

Cortana's predictions are generated by the same Bing Predicts system that

correctly predicted the outcomes of 15 of the 16 knockout stage games at this

year's World Cup soccer tournament. The tool uses an algorithm based on team

stats, home field advantage and weather. It also mines social media posts to

incorporate sentiment analysis. You can find predictions for this week's NFL

games on Cortana-enabled devices or at Bing.com.




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BIG DATA GROWTH INCREASES DATA INTEGRATIONDEGREE OF DIFFICULTY

Craig Stedman, Executive Editor

Technology is ever-changing. But perhaps the one thing IT teams can count

on is that the amount of data coming their way to manage will only continue to

increase. The numbers can be staggering: In a report published last December,

market research company IDC estimated that the total count of data created

or replicated worldwide in 2012 would add up to 2.8 zettabytes (ZB). For the

uninitiated, a zettabyte is 1,000 exabytes, 1 million petabytes or 1 billion tera-

bytes -- or, in more informal terms, a whole lotta data. By 2020, IDC expects

the annual data-creation total to reach 40 ZB, which would amount to a 50-fold

increase from where things stood at the start of 2010.

Corporate data expansion often starts with higher and higher volumes of

transaction data. But in many organizations, unstructured and semi-struc-

tured information -- the hallmark of big data environments -- is taking things

to a new level altogether. And because such data typically isn't a good fit for

relational databases and comes partly from external sources, big data growth




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also adds to the data integration workload -- and challenges -- for IT managersand their staffs.

SearchDataManagement recently published several articles that provide

insight and practical advice on managing integration projects involving large

amounts of data in general and big data in particular. In one, we look at the

key considerations that need to be taken into account on big data integration

initiatives. In another, we cover the complexities of integrating streaming sets

of big data. And in an interview, Glasshouse Technologies consultant Jim Da-

moulakis offers tips on planning and implementing integration efforts that can

accommodate big data growth.




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