Big Data
From Wikibon
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Big Data Research and Analysis from The Wikibon Project
The best of Wikibon's BigData research and analysis.
Big Data is emerging from the realms of data science projects to help companies understand exactly, make decisions, and act in real-time to better serve their customers and target markets. The IT techniques and tools to execute big data processing are new, very important and exciting.
Big Data is the new definitive source of competitive advantage across all industries. Enterprises and technology vendors that dismiss Big Data as a passing fad do so at their peril and, in our opinion, will soon find themselves struggling to keep up with more foreword-thinking rivals. For those organizations that understand and embrace the new reality of Big Data, the possibilities for new innovation, improved agility, and increased profitability are nearly endless.
The Big Data market is on the verge of a rapid growth spurt that will see it top the $50 billion mark worldwide within the next five years. The analysis in this article highlights Wikibon’s five-year forecast for the Big Data market as a whole
The Hadoop distribution race is important because no technology can achieve mass adoption in the enterprise unless risk-averse IT departments believe it will stand-up under pressure, and Hadoop is no exception. Consider the apocryphal saying, “Nobody ever got fired for buying IBM,” but replace IBM with Hadoop. Sounds almost fanciful, no? But making that statement a truism is now the mission of every Hadoop distribution vendor.
CIOs that believe they can survive and thrive in the Era of Big Data by making marginal improvements to existing data management technologies and infrastructures are mistaken. Rather, the enterprises that come to dominate the 21st century will be those that invest in new technologies and processes that allow them to ingest, analyze, and act on streaming data from all manner of sources in real-time and develop closed-loop feedback systems to continually optimize business processes.
Wikibon research in defining big data, to differentiate big data projects from traditional data warehousing projects and to look at the technical requirements. This Wikibon article looks at the business case for big data projects and compares them with traditional data warehouse approaches.
The Big Data ecosystem is exploding with slews of exciting start-ups. Below is a list of start-up vendors and the amount of venture capital each has raised, including lead investors. This list represents many of the top Big Data start-ups and Wikibon encourages community members to update this table with relevant start-ups and associated funding that are not already represented.
Additional Wikibon Big Data Research and Analysis
- Don’t Let Misconceptions Limit Your Hadoop Options
- Hardware Efficiency Important to Overall Hadoop ROI
- Accumulo: Why the World Needs Another NoSQL Database
- Google and VMware Provide Virtualization of Hadoop and Big Data
- Clearing Up Some Confusion on the Hadoop Wars
- Google Playing the Big Data Long Game
- The Emerging Big Data Vendor Ecosystem
- Ask More of Your Data, More Often
- The Big List of Big Data Infographics
- Google Playing the Big Data Long Game
- Big Data in 2012: Hadoop, Big Data Apps, Data Science Tools, Cloud Collision and More
- Predictions 2012: Big Data, Flash, Cloud and Facebook
- The Biggest Big Data Stories of 2011
- Definitive List of Big Data Statistics
- Navigating the Big Data Vendor Landscape
- Hadoop, Big Data Focus Shifting To Analytics and Visualization
- IBM Outperforms Even Apple: Smarter Planet, Big Data and Cloud Power the Future
- Data, VDI and Virtualization: 2011 IT Roadmaps
- Is Big Data Utopia Near at Hand?
- Ten “Big Data” Realities and What They Mean to You
- Strata Conference: The Big Data Wave is Coming
- Little Data, Big Data, Flash and Cloud Tiering: Predictions 2011
Big Data Peer Incites from The Wikibon Project
Live discussions between Big Data practitioners and the Wikibon community.
Where exactly does the value in Big Data lie? In a recent Wikibon Peer Incite call, Relay Technology Management’s Dr. Brigham Hyde zeroed in on the answer. Deriving value from Big Data, said Hyde, requires unifying unstructured content & data with structured data in a way that allows end-users to gain deeper insights than possible with analysis of structured data alone.
The Wikibon Community convened to consider whether the advent of Big Data with its focus on multiple kinds of data including unstructured data-types has turned the data warehouse into a dinosaur. The center piece of the discussion was a recent Wikibon study of the advantages and disadvantages of the Oracle Exadata IT appliance and similar offerings expected from IBM and HP, and a survey of early big data users.
Big Data Infographics from The Wikibon Project
Infographics and visualizations focused on Big Data and analytics.
Big Data can be a beast. Data volumes are growing exponentially. The types of data being created are likewise proliferating. And the speed at which data is being created – and the need to analyze it in near real-time to derive value from it – is increasing with each passing hour.
While the concept of data science has been around for decades, the notion of a data scientist has become an in-demand career leading to a rise of a new generation of data scientists. Social media platforms such as Facebook depend on data science to create innovative, interactive features that encourage users to get interested and stay that way. Here is a visual walk-through of this concept and the role of the data scientist.
What’s critical to realize is that 35% more digital information is created today than the capacity exists to store it; and this number will jump to over 60% over the next several years. Most of these gigabytes of data will pass through the servers, network, or routers of an enterprise, which becomes responsible at that moment for managing that content, protecting user privacy, watching over account information, and protecting copyright.
Big Data Videos from theCUBE and SiliconANGLE.tv
Collection of live Big Data event coverage and on-location reports.
SiliconANGLE and Wikibon filmed video at the opening of hack/reduce, a Big Data accelerator in Cambridge, Mass., on November 8, 2012.
Watch the full video here.
SiliconANGLE and Wikibon filmed two days of live video at Strata Conference + Hadoop World 2012 on October 24 & 25, 2012 in New York City.
Watch the full video here.
SiliconANGLE and Wikibon filmed two days of live video at IBM Information On Demand in Las Vegas, October 22 and 23, 2012.
Watch the full video here.
SiliconANGLE and Wikibon filmed two days of live video at Splunk .conf 2012 in Las Vegas, September 11 and 12, 2012.
Watch the full video here.
Original Content: SiliconANGLE and Wikibon filmed live video at Cassandra Summit in Santa Clara, Calif. on August 8, 2012.
Watch the full video here.
SiliconANGLE and Wikibon filmed two days of live video at Hadoop Summit in San Jose, Calif. June 13 and 14, 2012.
Watch the full video here.
SiliconANGLE and Wikibon filmed video at the Cambridge, Mass. Headquarters of Atlas Venture on May 27, 2012. 2012.
Watch the full video here.
SiliconANGLE and Wikibon filmed live video at HBaseCon 2012 in San Francisco on May 22, 2012.
Watch the full video here.
SiliconANGLE and Wikibon filmed three days of live video at EMC World and Data Science Summit in Las Vegas, May 21 through 23, 2012.
Watch the full video here.
SiliconANGLE and Wikibon filmed three days of live video at O'Reilly Strata Conference: Making Data Work 2012 in Santa Clara, Calif., Feb. 28 through Mar. 1, 2012.
Watch the full video here.
SiliconANGLE and Wikibon filmed two days of live video at Hadoop World 2011 in New York City, Nov. 8 & 9, 2011.
Watch the full video here.
SiliconANGLE and Wikibon filmed live video at Hadoop World 2010 in New York City, Oct. 12, 2010. 2011.
Watch the full video here.
Big Data Presentations from The Wikibon Project
Big Data presentation decks from Wikibon analysts.
A look at what Big Data is, the market opportunity, some customer use cases and how users should think about taking advantage of the opportunities. Especially targeted for explaining to an audience of infrastructure practitioners that the design requirements are different than traditional data center technologies.
View or download the full presentation here.
Big Data holds the potential to dramatically change the way enterprises do business across industries. Yet despite the enormous potential of Big Data, adoption among mainstream enterprises is relatively low. Find out what it will take to democratize Big Data.
View or download the full presentation here.
Additional Big Data Links and Resources
- Big Thoughts on Big Data by Wikibon's Jeff Kelly
- Big Data News from SiliconANGLE
- Big Data Channel on SiliconANGLE.tv
- SiliconANGLE.tv on YouTube
- (Forbes) Who Are The Top 20 Influencers in Big Data?
- Wikibon's Complete Archive of Big Data Professional Alerts
