Feb 28, 19: #AnalyticsClub #Newsletter (Events, Tips, News & more..)

[  COVER OF THE WEEK ]

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Data analyst  Source

[ AnalyticsWeek BYTES]

>> Big data: managing the legal and regulatory risks by analyticsweekpick

>> An Introduction to Apache Airflow and Talend: Orchestrate your Containerized Data Integration and Big Data Jobs by analyticsweekpick

>> Stream-based Data Integration – No Formatting Required by analyticsweek

Wanna write? Click Here

[ NEWS BYTES]

>>
 Financial Analytics Market Trends and Opportunities by types and Application in Grooming Regions; Edition 2018-2023 – The West Chronicle (press release) (blog) Under  Financial Analytics

>>
 Streaming Analytics Market Analysis, Outlook, Opportunities, Size, Share Forecast and Supply Demand 2018-2025 – The Smyrna Themes (press release) (blog) Under  Streaming Analytics

>>
 CVS Closes $69B Acquisition of Aetna, Altering Consumer Landscape – HealthPayerIntelligence.com Under  Health Analytics

More NEWS ? Click Here

[ FEATURED COURSE]

Process Mining: Data science in Action

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Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be ap… more

[ FEATURED READ]

Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

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Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the “data-analytic thinking” necessary for e… more

[ TIPS & TRICKS OF THE WEEK]

Strong business case could save your project
Like anything in corporate culture, the project is oftentimes about the business, not the technology. With data analysis, the same type of thinking goes. It’s not always about the technicality but about the business implications. Data science project success criteria should include project management success criteria as well. This will ensure smooth adoption, easy buy-ins, room for wins and co-operating stakeholders. So, a good data scientist should also possess some qualities of a good project manager.

[ DATA SCIENCE Q&A]

Q:What is a decision tree?
A: 1. Take the entire data set as input
2. Search for a split that maximizes the ‘separation” of the classes. A split is any test that divides the data in two (e.g. if variable2>10)
3. Apply the split to the input data (divide step)
4. Re-apply steps 1 to 2 to the divided data
5. Stop when you meet some stopping criteria
6. (Optional) Clean up the tree when you went too far doing splits (called pruning)

Finding a split: methods vary, from greedy search (e.g. C4.5) to randomly selecting attributes and split points (random forests)

Purity measure: information gain, Gini coefficient, Chi Squared values

Stopping criteria: methods vary from minimum size, particular confidence in prediction, purity criteria threshold

Pruning: reduced error pruning, out of bag error pruning (ensemble methods)

Source

[ VIDEO OF THE WEEK]

#FutureOfData with Rob(@telerob) / @ConnellyAgency on running innovation in agency

 #FutureOfData with Rob(@telerob) / @ConnellyAgency on running innovation in agency

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[ QUOTE OF THE WEEK]

War is 90% information. – Napoleon Bonaparte

[ PODCAST OF THE WEEK]

@TimothyChou on World of #IOT & Its #Future Part 2 #FutureOfData #Podcast

 @TimothyChou on World of #IOT & Its #Future Part 2 #FutureOfData #Podcast

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[ FACT OF THE WEEK]

Facebook users send on average 31.25 million messages and view 2.77 million videos every minute.

Sourced from: Analytics.CLUB #WEB Newsletter

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