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Prashanth Southekal, PhD's blog post was featured

Building the High Performing Team for Enterprise Data Analytics

Building the High Performing Team for Enterprise Data AnalyticsPrashanth Southekal and Santhosh RajuIntroductionHigh performing teams hold the key for the successful performance of any company. Whether you have thousands of employees or just five employees, high performing teams are a must for optimal business performance. Successful analytics initiatives are no exception and are also dependent on high performing teams. However, most Data Analytics teams today are a shadow of the old MIS/BI…See More

Nov 22

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Prasanth liked Prashanth Southekal, PhD's blog post Why Data Analytics is Heavy on Data Engineering?

Nov 6

Tim Matteson liked Prashanth Southekal, PhD's discussion Validation of the Prediction Model

Aug 16

Vincent Granville replied to Prashanth Southekal, PhD's discussion Validation of the Prediction Model

"The solution is cross-validation. See https://www.datasciencecentral.com/page/search?q=cross+validation"

Aug 16

Wasim replied to Prashanth Southekal, PhD's discussion Validation of the Prediction Model

"Model evaluation and validation measures vary depending on the modelling technique you use. "

Aug 15

eric Shi replied to Prashanth Southekal, PhD's discussion Validation of the Prediction Model

"when you validate a model, you should first consider model use fit the intended business purpose or not. Is the method used appropriate for the question, is the data appropriate for the model, is the model parameter estimation consistent with…"

Aug 15

Prashanth Southekal, PhD's discussion was featured

Validation of the Prediction Model

When there is a prediction model, apart from R-square, residuals etc. what are the different ways of performing validation of the prediction model? Basically,what are the different ways (apart from R-square, residuals etc.) where you are validating of your Analytics prediction model given that the real/actual values will be available only in future ?See More

Aug 12

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Prashanth Southekal, PhD posted a discussion

Validation of the Prediction Model

When there is a prediction model, apart from R-square, residuals etc. what are the different ways of performing validation of the prediction model? Basically,what are the different ways (apart from R-square, residuals etc.) where you are validating of your Analytics prediction model given that the real/actual values will be available only in future ?See More

Aug 12

3 Comments 1 Like

Prashanth Southekal, PhD posted a blog post

Data Standardization: The Core building block for Data Quality.

Data for Business Performance is using data in operations, compliance, and decision making. However, in most cases the available data in business enterprises is of poor quality. An article in Harvard Business Review (HBR) says – just 3% of the data in a business enterprise is of good quality. In this backdrop, what can be done to improve data quality? While there are many solutions to improve data quality, one option is to capture the important data entities i.e. master data using data…See More

May 9

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Prashanth Southekal, PhD's blog post was featured

Data Standardization: The Core building block for Data Quality.

Data for Business Performance is using data in operations, compliance, and decision making. However, in most cases the available data in business enterprises is of poor quality. An article in Harvard Business Review (HBR) says – just 3% of the data in a business enterprise is of good quality. In this backdrop, what can be done to improve data quality? While there are many solutions to improve data quality, one option is to capture the important data entities i.e. master data using data…See More

May 9

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Validation of the Prediction Model

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Prashanth Southekal, PhD's Page

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Building the High Performing Team for Enterprise Data Analytics

Validation of the Prediction Model

Validation of the Prediction Model

Data Standardization: The Core building block for Data Quality.

Data Standardization: The Core building block for Data Quality.

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Prashanth Southekal, PhD's Blog

Building the High Performing Team for Enterprise Data Analytics

Data Standardization: The Core building block for Data Quality.

Can Lack of Data Always Provide Valuable Insights?

Demystifying the Term Actionable Insights in Analytics

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