Analysis Learning Loss Matrix 
Cooperative Intelligence Blog
DECEMBER 28, 2016
Templates for Win/Loss Analysis – The Win Loss request I get asked the most often is, “Can you share your Win Loss templates?” I break down Win Loss analysis questions into 4 buckets: relationship health, company reputation, product/service attributes, and servicing issues. These topics are timeless.
Contify
SEPTEMBER 21, 2017
As a programmer with data science background, my attention is invariably caught by the real-world situations where machine learning algorithms have made a difference, for example: email spam filtering, news categorization, review based recommendations, social media sentiments etc. It’s a constant learning process.
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Contify
SEPTEMBER 21, 2017
As a programmer with data science background, my attention is invariably caught by the real-world situations where machine learning algorithms have made a difference, for example: email spam filtering, news categorization, review based recommendations, social media sentiments etc. It’s a constant learning process.
Elegant BI
MARCH 18, 2021
Outliers, also referred to as anomaly, exception, irregularity, deviation, oddity, arise in data analysis when the data records differ dramatically from the other observations. Dealing with Outliers: A secret ingredient for success of data analysis. Any kind of analysis initiates by looking upon the data. Outlier, an Outsider!
Datapine Blog
NOVEMBER 27, 2019
Today, most companies understand the impact of data quality on analysis and further decision-making processes and hence choose to implement a data quality management (DQM) policy, department, or techniques. DQM is indeed reckoned as the key factor in ensuring efficient data analysis, as it is the basis from where all the rest starts from.
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