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Mar 14, 19: #AnalyticsClub #Newsletter (Events, Tips, News & more..)
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Sourced from: Analytics.CLUB #WEB Newsletter
Mar 07, 19: #AnalyticsClub #Newsletter (Events, Tips, News & more..)
[ COVER OF THE WEEK ]
Pacman Source
[ AnalyticsWeek BYTES]
>> How Airbnb Uses Big Data And Machine Learning To Guide Hosts To The Perfect Price by analyticsweekpick
>> Underpinning Enterprise Data Governance with Machine Intelligence by jelaniharper
>> 2016 Trends for the Internet of Things: Expanding Expedient Analytics Beyond the Industrial Internet by jelaniharper
[ NEWS BYTES]
>>
Global Risk Analytics Market â Current & Future trends, Growth Opportunities, Industry analysis & forecast by 2025 – TechnoBust Under Risk Analytics
>>
Prescriptive Analytics Market- The Growing Prominence Of Big Data – CMFE News (press release) (blog) Under Prescriptive Analytics
>>
Prescriptive Analytics Market- The Growing Prominence Of Big Data – CMFE News (press release) (blog) Under Prescriptive Analytics
[ FEATURED COURSE]
Lean Analytics Workshop – Alistair Croll and Ben Yoskovitz
 |
Use data to build a better startup faster in partnership with Geckoboard… more |
[ FEATURED READ]
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
 |
[ TIPS & TRICKS OF THE WEEK]
Data Analytics Success Starts with Empowerment
Being Data Driven is not as much of a tech challenge as it is an adoption challenge. Adoption has it’s root in cultural DNA of any organization. Great data driven organizations rungs the data driven culture into the corporate DNA. A culture of connection, interactions, sharing and collaboration is what it takes to be data driven. Its about being empowered more than its about being educated.
[ DATA SCIENCE Q&A]
Q:Examples of NoSQL architecture?
A: * Key-value: in a key-value NoSQL database, all of the data within consists of an indexed key and a value. Cassandra, DynamoDB
* Column-based: designed for storing data tables as sections of columns of data rather than as rows of data. HBase, SAP HANA
* Document Database: map a key to some document that contains structured information. The key is used to retrieve the document. MongoDB, CouchDB
* Graph Database: designed for data whose relations are well-represented as a graph and has elements which are interconnected, with an undetermined number of relations between them. Polyglot Neo4J
Source
[ VIDEO OF THE WEEK]
#FutureOfData with Rob(@telerob) / @ConnellyAgency on running innovation in agency
Subscribe to Youtube
[ QUOTE OF THE WEEK]
In God we trust. All others must bring data. W. Edwards Deming
[ PODCAST OF THE WEEK]
Unconference Panel Discussion: #Workforce #Analytics Leadership Panel
Subscribe
[ FACT OF THE WEEK]
100 terabytes of data uploaded daily to Facebook.
Sourced from: Analytics.CLUB #WEB Newsletter
Feb 28, 19: #AnalyticsClub #Newsletter (Events, Tips, News & more..)
[ COVER OF THE WEEK ]
Correlation-Causation Source
[ AnalyticsWeek BYTES]
>> Big Data Facts by v1shal
>> 3 Big Data Stocks Worth Considering by analyticsweekpick
>> 10 Misconceptions about Big Data by v1shal
[ FEATURED COURSE]
 |
[ FEATURED READ]
The Future of the Professions: How Technology Will Transform the Work of Human Experts
 |
[ TIPS & TRICKS OF THE WEEK]
Fix the Culture, spread awareness to get awareness
Adoption of analytics tools and capabilities has not yet caught up to industry standards. Talent has always been the bottleneck towards achieving the comparative enterprise adoption. One of the primal reason is lack of understanding and knowledge within the stakeholders. To facilitate wider adoption, data analytics leaders, users, and community members needs to step up to create awareness within the organization. An aware organization goes a long way in helping get quick buy-ins and better funding which ultimately leads to faster adoption. So be the voice that you want to hear from leadership.
[ DATA SCIENCE Q&A]
Q:What is your definition of big data?
A: Big data is high volume, high velocity and/or high variety information assets that require new forms of processing
– Volume: big data doesnt sample, just observes and tracks what happens
– Velocity: big data is often available in real-time
– Variety: big data comes from texts, images, audio, video
Difference big data/business intelligence:
– Business intelligence uses descriptive statistics with data with high density information to measure things, detect trends etc.
– Big data uses inductive statistics (statistical inference) and concepts from non-linear system identification to infer laws (regression, classification, clustering) from large data sets with low density information to reveal relationships and dependencies or to perform prediction of outcomes or behaviors
Source
[ VIDEO OF THE WEEK]
Understanding #BigData #BigOpportunity in Big HR by @MarcRind #FutureOfData #Podcast
Subscribe to Youtube
[ QUOTE OF THE WEEK]
War is 90% information. – Napoleon Bonaparte
[ PODCAST OF THE WEEK]
@JohnTLangton from @Wolters_Kluwer discussed his #AI Lead Startup Journey #FutureOfData #Podcast
Subscribe
[ FACT OF THE WEEK]
And one of my favourite facts: At the moment less than 0.5% of all data is ever analysed and used, just imagine the potential here.
Sourced from: Analytics.CLUB #WEB Newsletter
Feb 21, 19: #AnalyticsClub #Newsletter (Events, Tips, News & more..)
[ COVER OF THE WEEK ]
Accuracy check Source
[ LOCAL EVENTS & SESSIONS]
- Mar 21, 2019 #WEB Data Analytics with Power BI â Best Features of 2018
- Feb 28, 2019 #WEB Free Machine Learning Intro Session – Los Altos CA
- Feb 28, 2019 #WEB Free Machine Learning Intro Session – Daly City CA
[ AnalyticsWeek BYTES]
>> Announcing dplyrXdf 1.0 by analyticsweekpick
>> Data Lakes: The Enduring Case for Centralization by jelaniharper
>> Social Media and the Future of Customer Support [Infographics] by v1shal
[ NEWS BYTES]
>>
Platform Virtualization Software Market Analysis, Share, Trends and Forecast 2025 â Industry Research Report 2018 – Journal of Industry Under Virtualization
>>
AWS Says It’s Never Seen a Whole Data Center Go Down – Data Center Knowledge Under Data Center
>>
CSP (CSPI) and Verint Systems (VRNT) Head-To-Head Survey – Fairfield Current Under Social Analytics
[ FEATURED COURSE]
Learning from data: Machine learning course
 |
[ FEATURED READ]
 |
[ TIPS & TRICKS OF THE WEEK]
Fix the Culture, spread awareness to get awareness
Adoption of analytics tools and capabilities has not yet caught up to industry standards. Talent has always been the bottleneck towards achieving the comparative enterprise adoption. One of the primal reason is lack of understanding and knowledge within the stakeholders. To facilitate wider adoption, data analytics leaders, users, and community members needs to step up to create awareness within the organization. An aware organization goes a long way in helping get quick buy-ins and better funding which ultimately leads to faster adoption. So be the voice that you want to hear from leadership.
[ DATA SCIENCE Q&A]
Q:How to detect individual paid accounts shared by multiple users?
A: * Check geographical region: Friday morning a log in from Paris and Friday evening a log in from Tokyo
* Bandwidth consumption: if a user goes over some high limit
* Counter of live sessions: if they have 100 sessions per day (4 times per hour) that seems more than one person can do
Source
[ VIDEO OF THE WEEK]
Subscribe to Youtube
[ QUOTE OF THE WEEK]
In God we trust. All others must bring data. W. Edwards Deming
[ PODCAST OF THE WEEK]
#FutureOfData Podcast: Peter Morgan, CEO, Deep Learning Partnership
Subscribe
[ FACT OF THE WEEK]
14.9 percent of marketers polled in Crain’s BtoB Magazine are still wondering ‘What is Big Data?’
Sourced from: Analytics.CLUB #WEB Newsletter
Feb 14, 19: #AnalyticsClub #Newsletter (Events, Tips, News & more..)
[ COVER OF THE WEEK ]
Statistically Significant Source
[ LOCAL EVENTS & SESSIONS]
- Feb 21, 2019 #WEB How to Build a Data Catalog to Smartly Exploit Your Data Assets
- Feb 21, 2019 #WEB Tutorials on “Deep Learning in R” on 3rd Thursdays Webinar- IST 6:00PM – 7:30PM
- Feb 21, 2019 #WEB Blockchain for Enterprise with Hyperledger Fabric by Murughan Palaniachari
[ AnalyticsWeek BYTES]
>> Oct 12, 17: #AnalyticsClub #Newsletter (Events, Tips, News & more..) by admin
>> Future of Public Sector and Jobs in #BigData World #FutureOfData #Podcast by v1shal
>> State of Data Warehouse: A GigaOm Market Landscape Report by analyticsweekpick
[ NEWS BYTES]
>>
Cisco and Amazon partner on hybrid-cloud approach – MarketWatch Under Hybrid Cloud
>>
Lack of analytics skill leads to over 76000 empty positions – People Matters Under Talent Analytics
>>
How data science is shaping the modern NHS – New Statesman Under Data Science
[ FEATURED COURSE]
 |
[ FEATURED READ]
How to Create a Mind: The Secret of Human Thought Revealed
 |
[ TIPS & TRICKS OF THE WEEK]
Data aids, not replace judgement
Data is a tool and means to help build a consensus to facilitate human decision-making but not replace it. Analysis converts data into information, information via context leads to insight. Insights lead to decision making which ultimately leads to outcomes that brings value. So, data is just the start, context and intuition plays a role.
[ DATA SCIENCE Q&A]
Q:Is it better to spend 5 days developing a 90% accurate solution, or 10 days for 100% accuracy? Depends on the context?
A: * premature optimization is the root of all evils
* At the beginning: quick-and-dirty model is better
* Optimization later
Other answer:
– Depends on the context
– Is error acceptable? Fraud detection, quality assurance
Source
[ VIDEO OF THE WEEK]
#BigData @AnalyticsWeek #FutureOfData #Podcast with Dr. Nipa Basu, @DnBUS
Subscribe to Youtube
[ QUOTE OF THE WEEK]
Data is not information, information is not knowledge, knowledge is not understanding, understanding is not wisdom. Clifford Stoll
[ PODCAST OF THE WEEK]
Want to fix #DataScience ? fix #governance by @StephenGatchell @Dell #FutureOfData #Podcast
Subscribe
[ FACT OF THE WEEK]
Every person in the US tweeting three tweets per minute for 26,976 years.
Sourced from: Analytics.CLUB #WEB Newsletter
Feb 07, 19: #AnalyticsClub #Newsletter (Events, Tips, News & more..)
[ COVER OF THE WEEK ]
Correlation-Causation Source
[ LOCAL EVENTS & SESSIONS]
- Feb 12, 2019 #WEB Open Data para entender la transformación de los barrios
- Feb 23, 2019 #WEB Artificial Intelligence – AI on Microsoft Platform
- Mar 06, 2019 #WEB Webinar – 8 Essential Tips for People Starting a Career in Data Science
[ AnalyticsWeek BYTES]
>> Why Is Big Data Is So Big In Health Care? by analyticsweek
>> Top 5 Lessons LEGO story teaches an entrepreneur by v1shal
>> Voices in Data Storage â Episode 3: A Conversation with Leo Leung of Oracle by analyticsweekpick
[ NEWS BYTES]
>>
Smarter AI: Machine learning without negative data – Science Daily Under Machine Learning
>>
Data center security company A10 Networks could be eyeing a sale – DatacenterDynamics Under Data Center
>>
How tech and data can spot and stop the quitters – Raconteur Under Sentiment Analysis
[ FEATURED COURSE]
Deep Learning Prerequisites: The Numpy Stack in Python
 |
[ FEATURED READ]
 |
[ TIPS & TRICKS OF THE WEEK]
Data Have Meaning
We live in a Big Data world in which everything is quantified. While the emphasis of Big Data has been focused on distinguishing the three characteristics of data (the infamous three Vs), we need to be cognizant of the fact that data have meaning. That is, the numbers in your data represent something of interest, an outcome that is important to your business. The meaning of those numbers is about the veracity of your data.
[ DATA SCIENCE Q&A]
Q:What do you think about the idea of injecting noise in your data set to test the sensitivity of your models?
A: * Effect would be similar to regularization: avoid overfitting
* Used to increase robustness
Source
[ VIDEO OF THE WEEK]
@DrewConway on creating socially responsible data science practice #FutureOfData #Podcast
Subscribe to Youtube
[ QUOTE OF THE WEEK]
The most valuable commodity I know of is information. Gordon Gekko
[ PODCAST OF THE WEEK]
@SidProbstein / @AIFoundry on Leading #DataDriven Technology Transformation #FutureOfData #Podcast
Subscribe
[ FACT OF THE WEEK]
Data is growing faster than ever before and by the year 2020, about 1.7 megabytes of new information will be created every second for every human being on the planet.
Sourced from: Analytics.CLUB #WEB Newsletter
Jan 31, 19: #AnalyticsClub #Newsletter (Events, Tips, News & more..)
[ COVER OF THE WEEK ]
Accuracy Source
[ LOCAL EVENTS & SESSIONS]
- Mar 01, 2019 #WEB Insights and Innovation Webinar Series: The Role of Digital in a Sustainable Built Environment
- Feb 07, 2019 #WEB Galvanize Data Science Information Session – Denver
- Feb 06, 2019 #WEB Analytical Method Validation and Transfer (wcs) A
[ AnalyticsWeek BYTES]
>> Startup Movement Vs Momentum, a Classic Dilemma by v1shal
>> Accelerating Discovery with a Unified Analytics Platform for Genomics by analyticsweek
>> Black Friday and Cyber Monday â Analyzing Your Holiday Numbers by analyticsweek
[ NEWS BYTES]
>>
Building a data security strategy â why the industry needs to work together – SC Magazine Under Data Security
>>
Global Prescriptive Analytics Market 2018 Growth, Production, Suppliers, Consumption, Region Forecast to 2023 – The West Chronicle (press release) (blog) Under Prescriptive Analytics
>>
New Master’s in Data Science Prepares Students for Fastest Growing Field in US – University of New Haven News Under Data Science
[ FEATURED COURSE]
 |
[ FEATURED READ]
The Black Swan: The Impact of the Highly Improbable
 |
[ TIPS & TRICKS OF THE WEEK]
Data aids, not replace judgement
Data is a tool and means to help build a consensus to facilitate human decision-making but not replace it. Analysis converts data into information, information via context leads to insight. Insights lead to decision making which ultimately leads to outcomes that brings value. So, data is just the start, context and intuition plays a role.
[ DATA SCIENCE Q&A]
Q:Explain selection bias (with regard to a dataset, not variable selection). Why is it important? How can data management procedures such as missing data handling make it worse?
A: * Selection of individuals, groups or data for analysis in such a way that proper randomization is not achieved
Types:
– Sampling bias: systematic error due to a non-random sample of a population causing some members to be less likely to be included than others
– Time interval: a trial may terminated early at an extreme value (ethical reasons), but the extreme value is likely to be reached by the variable with the largest variance, even if all the variables have similar means
– Data: cherry picking, when specific subsets of the data are chosen to support a conclusion (citing examples of plane crashes as evidence of airline flight being unsafe, while the far more common example of flights that complete safely)
– Studies: performing experiments and reporting only the most favorable results
– Can lead to unaccurate or even erroneous conclusions
– Statistical methods can generally not overcome it
Why data handling make it worse?
– Example: individuals who know or suspect that they are HIV positive are less likely to participate in HIV surveys
– Missing data handling will increase this effect as its based on most HIV negative
-Prevalence estimates will be unaccurate
Source
[ VIDEO OF THE WEEK]
#BigData @AnalyticsWeek #FutureOfData #Podcast with Dr. Nipa Basu, @DnBUS
Subscribe to Youtube
[ QUOTE OF THE WEEK]
Data are becoming the new raw material of business. Craig Mundie
[ PODCAST OF THE WEEK]
@DrewConway on fabric of an IOT Startup #FutureOfData #Podcast
Subscribe
[ FACT OF THE WEEK]
The data volumes are exploding, more data has been created in the past two years than in the entire previous history of the human race.
Sourced from: Analytics.CLUB #WEB Newsletter
Jan 24, 19: #AnalyticsClub #Newsletter (Events, Tips, News & more..)
[ COVER OF THE WEEK ]
Statistically Significant Source
[ LOCAL EVENTS & SESSIONS]
- Feb 02, 2019 #WEB Free Interactive Data Science webinar Using R | Take Your Career Places With Data Science
- Feb 06, 2019 #WEB Analytical Method Validation and Transfer (wcs) A
- Feb 21, 2019 #WEB [REPLAY] How To Design a Patient-Centered Mobile Health App
[ AnalyticsWeek BYTES]
>> 5 Natural Language Processing Techniques for Extracting Information by analyticsweek
>> Big Data: Are you ready for blast-off? by analyticsweekpick
>> The Evolution Of The Geek [Infographics] by v1shal
[ NEWS BYTES]
>>
The Future of US Data Security in the Wake of GDPR – Innovation & Tech Today (satire) (press release) (blog) Under Data Security
>>
HPE’s Composable Infrastructure No Longer Limited to Synergy Hardware – Data Center Knowledge Under Data Center
>>
93% of Healthcare Execs Seeking Improved Data Analytics, CDI – Health IT Analytics Under Health Analytics
[ FEATURED COURSE]
 |
[ FEATURED READ]
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
 |
[ TIPS & TRICKS OF THE WEEK]
Winter is coming, warm your Analytics Club
Yes and yes! As we are heading into winter what better way but to talk about our increasing dependence on data analytics to help with our decision making. Data and analytics driven decision making is rapidly sneaking its way into our core corporate DNA and we are not churning practice ground to test those models fast enough. Such snugly looking models have hidden nails which could induce unchartered pain if go unchecked. This is the right time to start thinking about putting Analytics Club[Data Analytics CoE] in your work place to help Lab out the best practices and provide test environment for those models.
[ DATA SCIENCE Q&A]
Q:How do you handle missing data? What imputation techniques do you recommend?
A: * If data missing at random: deletion has no bias effect, but decreases the power of the analysis by decreasing the effective sample size
* Recommended: Knn imputation, Gaussian mixture imputation
Source
[ VIDEO OF THE WEEK]
Subscribe to Youtube
[ QUOTE OF THE WEEK]
He uses statistics as a drunken man uses lamp postsfor support rather than for illumination. Andrew Lang
[ PODCAST OF THE WEEK]
@EdwardBoudrot / @Optum on #DesignThinking & #DataDriven Products #FutureOfData #Podcast
Subscribe
[ FACT OF THE WEEK]
100 terabytes of data uploaded daily to Facebook.
Sourced from: Analytics.CLUB #WEB Newsletter
Jan 17, 19: #AnalyticsClub #Newsletter (Events, Tips, News & more..)
[ COVER OF THE WEEK ]
Statistics Source
[ LOCAL EVENTS & SESSIONS]
- Jan 23, 2019 #WEB WEBINAR: De VSTS a Azure Devops: cambios y novedades
- Jan 22, 2019 #WEB Thinkful Online Info Session | Becoming a Data Scientist
- Jan 22, 2019 #WEB Develop a Successful Artificial Intelligence Tech Startup Business Today! – Entrepreneur Workshop – Bootcamp – Virtual Class – Seminar – Training – Lecture – Webinar – Conference
[ AnalyticsWeek BYTES]
>> 10 Techniques to Boost Your Data Modeling by analyticsweek
>> BDAS Analytics Suite Blends Big Data With HR by analyticsweekpick
>> Video: R and Python in in Azure HDInsight by analyticsweekpick
[ NEWS BYTES]
>>
Choosing the Right Data Catalog for Your Business – insideBIGDATA Under Business Analytics
>>
AMA Updates Population Health Tool to Improve Patient Care Access – Health IT Analytics Under Health Analytics
>>
Global Streaming Analytics Market 2018 Revenue, Potential Growth, Analysis, Price, Market Share, Growth Rate … – The West Chronicle (press release) (blog) Under Streaming Analytics
[ FEATURED COURSE]
Applied Data Science: An Introduction
|
[ FEATURED READ]
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
|
[ TIPS & TRICKS OF THE WEEK]
Analytics Strategy that is Startup Compliant
With right tools, capturing data is easy but not being able to handle data could lead to chaos. One of the most reliable startup strategy for adopting data analytics is TUM or The Ultimate Metric. This is the metric that matters the most to your startup. Some advantages of TUM: It answers the most important business question, it cleans up your goals, it inspires innovation and helps you understand the entire quantified business.
[ DATA SCIENCE Q&A]
Q:What does NLP stand for?
A: * Interaction with human (natural) and computers languages
* Involves natural language understanding
Major tasks:
– Machine translation
– Question answering: whats the capital of Canada?
– Sentiment analysis: extract subjective information from a set of documents, identify trends or public opinions in the social media
– Information retrieval
Source
[ VIDEO OF THE WEEK]
Advanced #Analytics in #Hadoop
Subscribe to Youtube
[ QUOTE OF THE WEEK]
Torture the data, and it will confess to anything. Ronald Coase
[ PODCAST OF THE WEEK]
#BigData #BigOpportunity in Big #HR by @MarcRind #JobsOfFuture #Podcast
Subscribe
[ FACT OF THE WEEK]
As recently as 2009 there were only a handful of big data projects and total industry revenues were under $100 million. By the end of 2012 more than 90 percent of the Fortune 500 will likely have at least some big data initiatives under way.