Big Data Analytics
This blog offers best practices and tips for companies looking toextract insight from internal data, plus today's most useful data from acrossthe Internet.
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Big data can lead to effective business process reformation
Specific big data can provide operational agility leading to the reformation of business processes and ultimately better performance.
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Why samples sizes are key to predictive data analytics
In order to use big data for predictive analytics, you must take sample sizes seriously and understand the risks about sampling assumptions.
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See if the R language fits in your big data toolkit
The R programming language could challenge SAS for big data queries. Get more details.
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Beat the odds in the big data productivity battle
Gartner predicts it will take companies five to ten years to achieve productivity with their big data. Learn six ways to avoid delaying productivity.
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Measure actual customer behavior using big data analytics
Discover how measuring actual customer behavior instead of behavioral intent can dramatically increase your marketing effectiveness.
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Redefining risk for big data
Machine-driven intelligence introduces risks that challenge traditional IT risk management. Here are three steps to take now.
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How to make big data actionable
C-levels want big data efforts to produce results and ROI. Here are three key points to keep in mind to fulfill these requests.
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Take our Big Data survey
We'd like to get your input on how your company has pursued the lure of Big Data and whether the steak has been worth the sizzle.
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IT's new role as big data stewards
Forward-thinking IT departments should take these four big data stewardship steps now.
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Database planning for big data modeling
When using sandboxes for your test databases, it's vital that a DBA provides guidelines for big data experimentation in that environment.
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Big data asset management: Engage traditional thinking to solve new problems
The IT asset management traditional playbook delivers value for big data. Here's what IT decision makers should consider about big data asset management.
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Use big data analytics to identify and retain your best customers
A big data strategy should include using analytics to identify your best customers and then offering them a free service to engender loyalty.
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Consider how to acculturate analytics workers to retain them
CIOs must get the proper role integration and teamwork in place for analytics workers in the data center before they start their employment.
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Big data spreadsheet products and their potential benefits
Excel isn't the most robust tool for big data work. Fortunately, there are spreadsheet solutions that fit the bill, and that may relieve some users' anxieties about big data.
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The best big data strategy is the strategy that keeps adapting
If human behavior undergirds your big data strategy, you must constantly be on alert for a shift in how your target is behaving.
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Measure actual customer behavior using big data analytics
Discover how measuring actual customer behavior instead of behavioral intent can dramatically increase your marketing effectiveness.
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Success is most likely when the data science team reports to IT
Regardless of how many big data initiatives companies have, most still find that they can only afford one data science team.
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Gain performance with big data analytics by overcoming stone-age software
The path toward more effective server utilization in data centers rests in software.
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Don't draw strategic conclusions from the wrong marketing data
If you're not careful, the data you're collecting for your marketing analysis may be telling you the wrong story about your target market.
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Call in a Black Belt to manage your big data analytics team
Even though it's tempting to embrace the latest and greatest theories on management, sometimes a leader needs to go old school to get the job done.
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Use big data analytics to identify and retain your best customers
A big data strategy should include using analytics to identify your best customers and then offering them a free service to engender loyalty.
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Why samples sizes are key to predictive data analytics
In order to use big data for predictive analytics, you must take sample sizes seriously and understand the risks about sampling assumptions.
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Apply Big Data to the email fight
Will Kelly looks at how Big Data technologies can be applied against a number of enterprise email issues now and in the future.
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Opportunity knocks with big data products
Instead of using big data only to sell, why not sell the output of your big data itself?
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The big data Dead Hand may not be the end of the world
Neither humans nor machines are infallible, but combining the two makes for a far more robust big data system than relying totally on just one.
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Big Data in your call center: Managing the numbers
The data collected by your call center software is huge and varied. But which metrics matter and how can you make changes based on those metrics?
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To get Big Data buy-in, IT should let go of proof of concept
If your company is currently experimenting with Big Data in an attempt to prove some sort of concept--interrupt this right away. If you're going to prove something--it better be value.
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Three applications of M2M and Big Data
Will Kelly points out three areas where Machine to Machine (M2M) technologies and Big Data are coming to together to deliver business results.
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Directory: Big data vendors in the US
TechRepublic's directory of big data vendors has market, product, and contact information on companies that provide data analytics, data warehousing, or other "big data" products and services.