Big Data. Big Decisions
InformationWeek
Special Coverage Series


10 Big Predictions About Big Data

Will big data be a force for good or evil by the end of this decade? See if you agree with expert reactions to new Pew Internet Center research.

Big Data Talent War: 10 Analytics Job Trends
Big Data Talent War: 10 Analytics Job Trends
(click image for larger view and for slideshow)
Will big data be a force for good or evil within a decade? Will humanity find new and innovative ways to analyze, visualize, and extract value from massive and growing data sets, or will we become overwhelmed by information that's simply too abundant to manage effectively?

These are just a few of the questions the Pew Internet Center's Internet & American Life Project and Elon University asked more than 1,000 Internet "experts," including educators, business executives, pundits, scientists, and other tech industry observers. "The Future of Big Data" survey posed a series of thought-provoking questions centered on one main theme: How will big data influence our lives in 2020?

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

The issue concerns government leaders as well. The White House Office of Science and Technology Policy announced in March the Big Data Research and Development Initiative, a plan by six federal agencies to spend more than $200 million to develop new tools to access, structure, and pull meaning from massive volumes of data.

With as murky a term as "big data" is, it's no surprise the responses to the Pew survey were varied. Optimists and pessimists offered their thoughts on the state of data analysis within a decade.

[ Will big data be good or bad for your company? Read one point of view: Why Big Is Bad When It Comes To Data. ]

We've posted some of the more thought-provoking responses below. Respondents were free to agree or disagree with each statement, and explain why. The full set of survey predictions is available here.

Pew survey statement: "By 2020, the use of Big Data will improve our understanding of ourselves and the world."

Sean Mead, director of analytics at Mead, Mead & Clark, Interbrand, believes big data may be the next tech boom: "Large, publicly available data sets, easier tools, wider distribution of analytics skills, and early stage artificial intelligence software will lead to a burst of economic activity and increased productivity comparable to that of the Internet and PC revolutions of the mid to late 1990s."

"Big data is the new oil," wrote Bryan Trogdon, an entrepreneur and user-experience professional. "The companies, governments, and organizations that are able to mine this resource will have an enormous advantage over those that don't."

Survey statement: "Nowcasting, real-time data analysis, and pattern recognition will surely get better."

Google chief economist Hal Varian agrees that real-time forecasting has a bright future: "I'm a big believer in nowcasting," he wrote. "Nearly every large company has a real-time data warehouse and has more timely data on the economy than our government agencies. In the next decade we will see a public/private partnership that allows the government to take advantage of some of these private-sector data stores. This is likely to lead to a better informed, more pro-active fiscal and monetary policy."

Survey statement: "The good of big data will outweigh the bad. User innovation could lead the way, with "do-it-yourself analytics."

Marjory S. Blumenthal, associate provost at Georgetown University and adjunct staff officer at RAND, sees the pros and cons of advancements in data analysis tools and techniques. "Do-it-yourself analytics will help more people analyze and forecast than ever before. This will have a variety of societal benefits and further innovation. It will also contribute to new kinds of crime," Blumenthal wrote.

 1 | 2  | Next Page »


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

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

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.