IoT Devices

Introduction to Data Science

June 3, 2017 Analytics, Big Data, Big Data Analytics, Big Data Management, Cloud Computing, Cold Path Analytics, Data Analytics, Data Collection, Data Hubs, Data Science, Data Scientist, Edge Analytics, Emerging Technologies, Hot Path Analytics, Human Computer Interation, Hype vs. reality, Industrial Automation, Internet of Nano Things, Internet of Things, IoT, IoT Devices, Keyword Analysis, KnowledgeBase, Machine Learning(ML), machine-to-machine (M2M), Machines, Predictive Analytics, Predictive Maintenance, Realtime Analytics, Robotics, Sentiment Analytics, Stream Analytics No comments

We all have been hearing the term Data Science and Data Scientist occupation become more popular these days. I thought of sharing some light into this specific area of science, that may seem interesting for rightly skilled readers of my blog. 

Data Science is one of the hottest topics on the Computer and Internet  nowadays. People/Corporations have gathered data from applications and systems/devices until today and now is the time to analyze them. The world wide adoption of Internet of Things has also added more scope analyzing and operating on the huge data being accumulated from these devices near real-time.

As per the standard Wikipedia definition goes Data science, also known as data-driven science, is an interdisciplinary field about scientific methods, processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.”.

Data Science requires the following skillset:

  • Hacking Skills
  • Mathematics and Statistical Knowledge
  • Substantive Scientific Expertise

aoz1BJy

[Image Source: From this article by Berkeley Science Review.]

Data Science Process:

Data Science process involves collecting row data, processing data, cleaning data, data analysis using models/algorithms and visualizes them for presentational approaches.  This process is explained through a visual diagram from Wikipedia.

Data_visualization_process_v1

[Data science process flowchart, source wikipedia]

Who are Data Scientist?

Data scientists use their data and analytical ability to find and interpret rich data sources; manage large amounts of data despite hardware, software, and bandwidth constraints; merge data sources; ensure consistency of datasets; create visualizations to aid in understanding data; build mathematical models using the data; and present and communicate the data insights/findings.

They are often expected to produce answers in days rather than months, work by exploratory analysis and rapid iteration, and to produce and present results with dashboards (displays of current values) rather than papers/reports, as statisticians normally do.

Importance of Data Science and Data Scientist:

“This hot new field promises to revolutionize industries from business to government, health care to academia.”

The New York Times

Data Scientist is the sexiest job in the 21st century as per Harward Business Review.

McKinsey & Company projecting a global excess demand of 1.5 million new data scientists.

What are the skills required for a Data Scientist, let me share you a visualization through a Brain dump.

FxsL3b8

I thought of sharing an image to take you through the essential skill requirements for a Modern Data Scientist.

So what are you waiting for?, if you are rightly skilled get yourselves an Data Science Course.

Informational  Sources:

IoT Central–Microsoft’s SaaS solution for IoT

April 25, 2017 AMQP, Analytics, Azure, Azure IoT Suite, Cloud Computing, Cloud Services, Cloud to Device, Communication Protocols, Connected, Connectivity, Device to Cloud, Emerging Technologies, HTTP 1.1, Identity of Things (IDoT), Intelligent Cloud, Intelligent Edge, Internet of Things, IoT, IoT Central, IoT Devices, IoT Edge, IoT Hub, IoT Privacy, IoT Security, Machines, MQTT, PaaS, SaaS, Stream Analytics No comments

Microsoft has today released their IoT SaaS offering for customers and partners called as “Microsoft IoT Central”.  IoT Central enables powerful IoT scenarios without requiring cloud solution expertise and also simplifies the development process and makes customers to make quick time to market solutions, making digital transformation more accessible to everyone without overhead of implement solutions end to end.

As per Microsoft :

“IoT Central provides an easier way to create connected products that propel digital business. Take the complexity out of the Internet of Things (IoT) with a true, end-to-end IoT software as a service (SaaS) solution in the cloud that helps you build, use, and maintain smart products.”

Benefits of IoT Central:

  • Proven platform and technology with enterprise grade security.
  • Reduced complexities of setting up and maintaining IoT infrastructure and solutions.
  • Building smart connected products with lesser cost  and lesser overhead would ensure higher customer satisfaction.
  • Quickly adapt to changing environments.

For those would need control on implementing end to end can still choose the PaaS solution Azure IoT Suite.

Below is a picture from @JanakiramMSV’s article from forbes.com, to help you have a high level look at all the IoT offerings from Microsoft.

az-iot

Sources: