Big Data. Big Decisions
InformationWeek
Special Coverage Series


Big Data Talent Quandary: In-House Or Outsource?

Data scientists are hard to find, but outsourcing may help, says Hewlett-Packard exec.

 Big Data Talent War: 7 Ways To Win
Big Data Talent War: 7 Ways To Win
(click image for larger view and for slideshow)
To compete effectively in an increasingly data-driven world, businesses need to leverage all the data that's essential to their operations, and to invest in people and platforms to pull strategic insights from a rising stockpile of information.

If a company lacks the resources, or the interest, to build an in-house big data analytics team, it could always outsource the job to a third-party service provider. Hewlett Packard's business process outsourcing (BPO) division, for instance, provides business analytics services designed to deliver data-driven insights to enterprises.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

In a phone interview with InformationWeek, Arindam Dutta, general manager and director of HP's Asia Pacific and Japan BPO unit, said that finding big data talent -- specifically people with the right mix of technical know-how and business knowledge -- is a complex issue facing businesses today. "It's definitely the biggest challenge right now," said Dutta. "It's about finding the right talents, and finding them in abundance."

[ For more on the big data outsourcing dilemma, see Should You Outsource Your Data Scientist? ]

A unique skill set is required to process vast and varied volumes of data, one that goes beyond a graduate degree in advanced analytics. "It's about deploying the right people, which is not necessarily about having just a statistical and mathematical background, but also about having industry knowledge," said Dutta. "It's about making sense of the data and having some meaningful insights that the company can use."

A recent HP white paper with research from Gartner estimates that only 13% of companies currently use predictive analytics extensively, and less than 3% use prescriptive capabilities such as decision/mathematical modeling, simulation, and optimization. And while those percentages are rising, they suggest that most organizations have yet to embrace advanced analytical tools.

A shortage of trained technicians is one reason for the low figures, Dutta believes, but so is the fact that many companies lack a carefully planned big data strategy. "It's about putting together an entire roadmap -- not just doing isolated things here or there, but putting the entire ecosystems in place."

Companies' reluctance to implement big data platforms provides an opportunity for BPO service providers like HP, which can pitch its analytics services not as a cheaper alternative to an in-house team of data scientists, but as a new solution to solve a company's big data problems. "From an outsourcing or BPO point of view, it's not about a service provider going to the client and saying, 'You've got a standard process of analytics. You've got 10 guys doing it. I can do that a lot cheaper,'" Dutta explained. "We are talking about a situation where we are going to a client, and painting a picture of where they are right now." The service provider then shows how it can deploy tools and talent to (hopefully) help the client achieve its data-related goals.

One big data trend to watch is the consumerization of advanced analytics, such as improved user interfaces with gesture and/or voice recognition. Friendlier UIs will allow wider adoption and impact of data analytics, according to the HP/Gartner paper. For instance, voice-enabled controls similar to Apple's Siri will migrate from consumer to enterprise hardware, the report predicts, bringing voice interaction to advanced analytic applications.

In addition, increasingly powerful mobile devices -- including phones, tablets, sensors, and other connected hardware -- will enable robust analytic processing at the "point of decision or action," such as at repair or maintenance facility. "Consumerization is the key to making advanced analytics more accessible to a broader set of users; however, new processes for building advanced analytics must also be implemented," the study says.

Attend Interop Las Vegas May 6-10, and be the first to create an action plan to incorporate the latest transformative technologies into your IT infrastructure. Use Priority Code DIPR01 by Jan. 13 to save up to $800 with Super Early Bird Savings. Join us in Las Vegas for access to 125+ workshops and conference classes, 350+ exhibiting companies and the latest technology solutions. Register for Interop today!



Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

Pie Chart: Formal Big Data Strategy

Data: InformationWeek 2012 Big Data Survey of 231 business technology professionals, December 2011

What Do You Think?

Which group is the primary user of your organization's data?
Department-level analysts
Senior business management
A wide array of business users
Dedicated business analyst group
Business users dedicated to analysis (not full time)
Others



Related Content

From Our Sponsor

Big Data: Harnessing a Game-Changing Asset

Big Data: Harnessing a Game-Changing Asset

Big data is changing the way companies of all sizes go about their business by unlocking insight. Find out what they are saying about the impact data has had on their organization in the past five years, and the future agenda.

Big Data Meets Big Data Analytics

Big Data Meets Big Data Analytics

The vision of big data is that organizations will harvest every byte of relevant data and make superior decisions. Explore how big data technologies not only support the ability to collect large amounts, but provide the ability to take advantage of its full value.

The Chief Merits of Hadoop

The Chief Merits of Hadoop

Companies founded by Hadoop contributors, provide validated software builds and enterprise support contracts for organizations that aren't comfortable with unsupported open-source software. Find out why many US Fortune 500 companies have either completed or are planning a project involving Hadoop.

High-Performance Analytics Makes the Difference

High-Performance Analytics Makes the Difference

How do you solve your biggest big data problems? If you focus on the analytic rather than a transactional basis, you need high-performance analytics. Explore what you could do differently if you drastically reduce processing times for fraud, risk, marketing and collections.

4 Recommendations to Guide Business Intelligence Purchases

4 Recommendations to Guide Business Intelligence Purchases

Next-generation BI tools blend the capabilities of top-down, metrics-driven reporting with bottom-up, ad hoc analyses seamlessly. Read this white paper to learn about 4 key recommendations that will prepare you for your next BI Purchase.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.