Beth Schultz

Keeping Your Cool With Big-Data Analytics

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BethSchultz
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Re: Experimentation with Big Data
BethSchultz   5/21/2012 3:47:28 PM
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Hi MDMConsult -- I'm curious, would you say this is more important these days, with big-data all around us, or simply more of the same (but with  more data at our disposal)?

MDMconsult
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Experimentation with Big Data
MDMconsult   5/21/2012 3:39:02 PM
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@Beth This is very true, Experimentation with Big Data is good. How to solidify these concepts is important in the new work environments with Big Data. "Test and Learn"

BethSchultz
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Re: Keeping Your Cool With Big-Data Analytics
BethSchultz   5/21/2012 10:17:36 AM
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SaneIT, I absolutely agree. Companies today need to allow for experimentation and exploration of big-data, internal and external. The everyday analytics projects need to get done, of course, but companies that don't allow for innovative use of their analytics capabilities and data aren't thinking competitively enough.

Anish
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Re: What if value cannot be derived
Anish   5/21/2012 9:52:22 AM
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@Altaf  All the raw data processing to make it woth for analysis would take place in step 2.

SaneIT
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Re: Keeping Your Cool With Big-Data Analytics
SaneIT   5/21/2012 8:14:24 AM
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"Another approach is to explore data proactively and experiment to see what analytics it can drive."  This makes a lot of sense, rather than getting overwhelmed by a big data set playing with it to see what you can get out is a good strategy. Even if you can't use it for your current project you'll know what you can pull from it and it might reveal some data that doesn't replace up but supports your other data.

 

ahdand
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Re: What if value cannot be derived
ahdand   5/21/2012 1:11:17 AM
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It might be difficult at the beginning but by digging deep into analytics especially when you dig into raw data it is interesting

WaqasAltaf
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Re: What if value cannot be derived
WaqasAltaf   5/19/2012 11:55:18 PM
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@ Anish

Thanks for enlisting the analysis' steps. I agree that proper database management techniques can solve the problem of having allocate considerable time and effort to identify what data is all about. Though, still data can be in a raw form if it is extracted from an external source. Fine tuning will be required from step 1 to find out its value as the extractor has no control over the form of data kept by the source. 

Anish
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Re: What if value cannot be derived
Anish   5/19/2012 3:32:39 PM
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Hi Atlaf- The problem you addressed is a data insufficiency issue. I think an Analyst should categorize his analysis into three steps:

1. Specification gathering and data requirement

2. Data Audit and Preparation

3. Modeling and Visualization

The optimization of first two steps using data source configuration (mapping with third party sources) and proper database management techniques (cleaning and validation) using ETL tools can solve the problem to a major extent.

Anish
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Data is the NEED not an OVERHEAD
Anish   5/19/2012 3:25:29 PM
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Thanks for sharing this insight with us Beth. I totally second Franks on the importance of insight driven analytics. The objective for any analysis is usually predefined and calls for data requirements, big or small, which drive the process as the first step towards providing business recommendations. Big data also sometimes offers scope of approaching the problem much more creatively and innovate by exploiting the extra information available from the data.

 

WaqasAltaf
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Data Doctor
What if value cannot be derived
WaqasAltaf   5/19/2012 11:50:59 AM
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Its true that allocating value to big data can help determine whether advanced techniques/tools need to be applied and considerable time can be devoted to make the data usable for producing analytics which can further derive value to business. However, in many cases, the data is not even in a condition where the expected value of it can be predicted. First the data has to be aligned in a structured way and then it can be estimated that what value it can have if analytics can be applied to it. 

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