The Internet of Things remains one of the hottest trends in technology. Here's how the demand is translating to salaries for experienced professionals.
Good if you want to know what skills and roles you need to aim towards in your own career.
This is a blog containing data related news and information that I find interesting or relevant. Links are given to original sites containing source information for which I can take no responsibility. Any opinion expressed is my own.
Tuesday, 31 October 2017
Monday, 30 October 2017
How to Spot a Machine Learning Opportunity, Even If You Aren’t a Data Scientist by Kathryn Hume via @HarvardBiz
Having an intuition for how machine learning algorithms work - even in the most general sense - is becoming an important business skill.
Interesting and definitely worth a read.
Interesting and definitely worth a read.
Sunday, 29 October 2017
Graph Databases Help Companies Unlock Connections Within Their Data by Tom Smith via @DZone
Once you become familiar with graph databases, you’ll expand your view of how to ingest and analyse unstructured data at speeds you cannot imagine.
This is in the form of an interview with Jim Webber, Chief Scientist at Neo4j. Really interesting.
This is in the form of an interview with Jim Webber, Chief Scientist at Neo4j. Really interesting.
Saturday, 28 October 2017
The Python and R Graph Gallery by/via @R_Graph_Gallery
This could be handy for your next Python or R data viz project: hundreds of charts along with the reproducible R and Python code.
Something to bookmark and keep for the next time you need to find a a great chart for your data.
Something to bookmark and keep for the next time you need to find a a great chart for your data.
Friday, 27 October 2017
WEBINAR: Predictive Forecasting with Time Series Analysis - 7 November 2017

Overview
Title: Predictive Forecasting with Time Series Analysis
Date: Tuesday, November 07, 2017
Time: 09:00 AM Pacific Standard Time
Duration: 1 hour
Summary
Predictive Forecasting with Time Series Analysis
The ability to accurately predict what is likely to happen at a point in the future, and build plans and strategies based on that knowledge, is essential to an organization’s success. But what happens when a forecast is inaccurate? What is the impact on a business, its customers or its partners? For businesses, the ability to catch even a tiny glimpse of what the future may hold can lead to happy customers, improved efficiency and productivity, and highly successful business decisions.
In this Data Science Central webinar learn how time series analysis better enables departments across your organization with actionable, more accurate insights related to the timing of equipment failure, customer offers, and the impact of effects like seasonality.
Speakers:
Murali Prakash, IBM Product Manager -- IBM SPSS
Mikhail Lakirovich, IBM Offering Manager -- IBM SPSS
Douglas Stauber, IBM Offering Manager -- IBM SPSS
Mikhail Lakirovich, IBM Offering Manager -- IBM SPSS
Douglas Stauber, IBM Offering Manager -- IBM SPSS
Hosted by:
Bill Vorhies, Editorial Director -- Data Science Central

The Seven Deadly Sins of AI Predictions by Rodney Brooks via @techreview
"Mistaken extrapolations, limited imagination, and other common mistakes that distract us from thinking more productively about the future."
Great list and I agree with them 100%
Great list and I agree with them 100%
Thursday, 26 October 2017
The top MDM and data governance consultancies by David Weldon via @infomgmt
The Master Data Management Institute offers its picks for the top global and regional systems integrators, and advice on how organisations can best work with them.
Great lists of consultancies and integrators for MDM.
Great lists of consultancies and integrators for MDM.
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