Big Data
From Wikibon
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A complete archive of big data analysis, coverage, and content marketing news and information from the team at Wikibon and SiliconANGLE. | A complete archive of big data analysis, coverage, and content marketing news and information from the team at Wikibon and SiliconANGLE. | ||
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| - | [[Image:BigDataComponents.JPG|right|thumb|100px]] | + | [[Image:BigDataComponents.JPG|right|thumb|100px]]<b>[http://wikibon.org/wiki/v/Enterprise_Big-data The Definition of Enterprise Big Data]</b> |
| - | <b>[http://wikibon.org/wiki/v/Enterprise_Big-data The Definition of Enterprise Big Data]</b> | + | |
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 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. | ||
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| - | [[Image:bigdatachrac.png|left|thumb|100px|]] | + | [[Image:bigdatachrac.png|left|thumb|100px|]]<b>[http://wikibon.org/wiki/v/Big_Data:_Hadoop,_Business_Analytics_and_Beyond A Big Data Manifesto from the Wikibon Community]</b> |
| - | <b>[http://wikibon.org/wiki/v/Big_Data:_Hadoop,_Business_Analytics_and_Beyond A Big Data Manifesto from the Wikibon Community]</b> | + | |
Providing effective business analytics tools and technologies to the enterprise is a top priority of CIOs. Effective business analytics allows organizations to extract insights from corporate data to deliver higher levels of efficiency and profitability to the enterprise. Underlying every business analytics practice is data. | Providing effective business analytics tools and technologies to the enterprise is a top priority of CIOs. Effective business analytics allows organizations to extract insights from corporate data to deliver higher levels of efficiency and profitability to the enterprise. Underlying every business analytics practice is data. | ||
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| - | [[Image:BigDataMarketForecast2012.png|right|thumb|100px]] | + | [[Image:BigDataMarketForecast2012.png|right|thumb|100px]]<b>[http://wikibon.org/wiki/v/Big_Data_Market_Size_and_Vendor_Revenues Big Data Market Size and Vendor Revenues]</b> |
| - | <b>[http://wikibon.org/wiki/v/Big_Data_Market_Size_and_Vendor_Revenues Big Data Market Size and Vendor Revenues]</b> | + | |
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 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 | ||
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| - | [[Image: MPPvsDW Figure1.JPG | + | [[Image: MPPvsDW Figure1.JPG|left|100px]]<b>[http://wikibon.org/wiki/v/Financial_Comparison_of_Big_Data_MPP_Solution_and_Data_Warehouse_Appliance Comparison of Big Data MPP Solution & Data Warehouse Appliance]</b> |
| - | <b>[http://wikibon.org/wiki/v/Financial_Comparison_of_Big_Data_MPP_Solution_and_Data_Warehouse_Appliance Comparison of Big Data MPP Solution & Data Warehouse Appliance]</b> | + | |
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. | 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. | ||
Revision as of 02:49, 13 March 2012
Curated Big Data Coverage & Analysis
A complete archive of big data analysis, coverage, and content marketing news and information from the team at Wikibon and SiliconANGLE.
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.
Providing effective business analytics tools and technologies to the enterprise is a top priority of CIOs. Effective business analytics allows organizations to extract insights from corporate data to deliver higher levels of efficiency and profitability to the enterprise. Underlying every business analytics practice is data.
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
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.
Additional Big Data Analysis
Big Data Blog Posts from the Wikibon Community
- 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
- 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
Additional Links and Resources
