Stream Analytics

Big Data & Front End Development track in the Microsoft Professional Program

June 8, 2017 Analytics, Azure, Azure Data Factory, Azure Data Lake, Big Data, Big Data Analytics, Big Data Management, Data Analytics, Data Services, Emerging Technologies, Hadoop, HD Insight, IaaS, PaaS, Predictive Analytics, Realtime Analytics, SQL Azure, Stream Analytics, Windowz Azure No comments

Earlier I introduced you the Microsoft Professional Program for Data Science. Right after few days Microsoft announced the BETA availability of two more tracks Big Data and Front End Development.

Big Data Track:

This Microsoft program will help you to learn necessary skills from cloud storage and databases to Hadoop, Spark, and managed data services in Azure. Curriculum of this program involves learning how to build big data solutions for batch and real-time stream processing using Azure managed services and open source systems like Hadoop and Spark.

Are you intend to pursue a Data Analytics career, this is the right program for you to gain necessary insights.

Technology you will apply to gain these skills are: Azure Data Lake, Hadoop, HDInsight, Spark, Azure data factory, Azure Stream Analytics

Below is the course outline :

  • 10 COURSES  |  12-30  HOURS PER COURSE  |  8  SKILLS
  • ENROLL NOW here
  • More details here

Front End Development Track:

This track provides you necessary skills to get started with Advanced Front End development using HTML5, CSS3, JavaScript, AngularJS and Bootstrap.  At the end of the curriculum you will become master in Front End Development with all predominant modern web technologies.

So if you are a front end UI developer, this is something you can try out to enhance your skills.

Below is the course outline :

  • 13 COURSES  |  15-30 HOURS PER COURSE  |  11 SKILLS
  • ENROLL NOW here
  • More details  here

Track detail

Each course runs for three months and starts at the beginning of a quarter. January—March, April—June, July—September, and October —December. The capstone runs for four weeks at the beginning of each quarter: January, April, July, October. For exact dates for the current course run, please refer to the course detail page on edX.org. 

[Microsoft]

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

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[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.

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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:

Azure in Germany–a complete EU cloud computing solution

May 18, 2017 .NET, Analytics, AppFabric, Azure, Azure in Germany, Azure IoT Suite, Cloud Computing, Cloud Services, Cloud Strategy, Cognitive Services, Computing, Data Analytics, Data Governance, Data Hubs, Data Warehouse, Emerging Technologies, Event Hubs, IaaS, Intelligent Edge, Internet of Things, IoT, IoT Central, IoT Hub, Machine Learning(ML), Media Services, Media Services & CDN, Messaging, Microsoft, Mobile Services, PaaS, SaaS, SQL Azure, Storage, Backup & Recovery, Stream Analytics, Virtual Machines, Windowz Azure No comments

With my earlier article Azure in China, it came in to my interest to look for any other country/region specific independent cloud data center requirements.  I came across Azure for US Govt(Similar to Amazon Govt Cloud) instance and Azure Germany data center.  For this article context I will be covering only Azure in Germany.

What is Azure Germany?

Just like regional regulatory requirements in China, Germany also wanted a completely locally owned/managed Azure Data Center for EU/EFTA/UK requirements. This is also to ensure stricter access control and data access policy measurements. This  approach is to enable organizations doing business in EU/EFTA and UK can better harness the power of cloud computing.

  • All customer data and related applications and hardware reside in Germany
  • Geo-replication between datacenters in Germany to support  business continuity
  • Highly secured datacenters provide 24×7 monitoring
  • It meets all Public sector or restricted industry requirements
  • Follows all Compliance requirements for EU/EFTA and UK.
  • Lower cost, locally accessible  within your business locations in Germany/EU.

“ Azure Germany is an isolated Azure instance in Germany, independent from other public clouds.”

Who controls it?

An independent data trustee controls access to all customer data in the Azure Germany datacenters. T-Systems International GmbH, a subsidiary of Deutsche Telekom and an experienced, well-respected IT provider incorporated in Germany, serves as trustee, protecting disclosure of data to third parties except as the customer directs or as required by German law.

** Even Microsoft does not have access to customer data or the datacenters without approval from and supervision by the German data trustee.

What Compliance?

Azure Germany has an ongoing commitment to maintaining the strictest data protection measures, so organizations can store and manage customer data in compliance with applicable German laws and regulations, as well as key international standards. Additional compliance standards and controls that address the unique role of the German data trustee will be audited over time. Refer to: Microsoft Trust Center compliance.

[Source : Microsoft Azure]

Useful Links:

Introducing Azure IoT Edge

May 13, 2017 .NET, Analytics, Artificial Intelligence(AI), Augmented Reality, Azure, Azure IoT Suite, Cloud Computing, Data Analytics, Edge Analytics, Embedded, Emerging Technologies, Event Hubs, Industrial Automation, Intelligent Cloud, Intelligent Edge, IoT, IoT Edge, IoT Hub, Linux, Mac OSX, Machine Learning(ML), Microsoft, Robotics, Self Driven Cars, Stream Analytics, Windows, Windowz Azure No comments

During Build! 2017 Microsoft has announced the availability of Azure IoT Edge, which would bring in some of the cloud capabilities to edge devices/networks within your Enterprise. This would enable industrial devices to utilize the capabilities of IoT in Azure within their constrained resources . 

With this Microsoft now makes it easier for developers to move some of their computing needs to these devices.  Edge devices are mostly having small foot print based to high end machines within your company network.

The essential capabilities to be supported by Azure IoT edge  include:

  • Perform Edge Analytics (a cut down version of Azure Stream Analytics)- Instead of doing analytics in cloud developer/implementer can move the basic cloud data processing and analytical capabilities to Edge Device. Run your machine learning algorithms in Edge device and take predictive analytics steps.
  • Perform Artificial Intelligence processing at edge device itself. Availability of Microsoft Cognitive Service on edge device would bring in whole lot of automation capabilities. Imagine Alexa/Siri working without internet connection, it should be able to provide you reminders etc.
  • Perform RealTime Decision making locally based on predefined rules.
  • Reduce bandwidth costs
  • Connect to other Edge devices and legacy devices within the constrained/corporate network.
  • Deploy IoT solutions to Edge Device from Cloud and provide updates as needed.
  • Operate offline without the need of real-time internet connectivity or intermittent connectivity. Doesn’t have to rely on Cloud to provide commands for processing, can do offline data capture and processing of information from other devices connected and take decisions without the need to rely on a connected cloud service.

Azure IoT Edge enables seamless deployment of cloud services such as:

Along with sharing the image represents Azure’s Enterprise Digital Vision, we will discuss about the same in later sessions:

Digital-Enterprise-Vision_png

Getting Started & More information:

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:

Microsoft Azure IoT Suite–Provisioned solutions for Faster Time to Market IoT enabled solutions

January 7, 2017 Analytics, Azure, Azure SDK, Cloud Computing, Communication Protocols, Contrained Networks/Devices, Data Collection, Data Integration, Emerging Technologies, Identity of Things (IDoT), Internet of Things, Interoperability, IoT, PaaS, Performance, Predictive Analytics, Predictive Maintenance, Realtime Analytics, Reliability, Scalability, Self Driven Cars, Solutions, Stream Analytics, Tech-Trends, Windowz Azure No comments

Microsoft Azure IoT Suite Provisioned solutions will help you create your own fully integrated solutions tailored for your specific needs in the following 3 sections. Using these ready to consume solutions will accelerate your time to market IoT(Internet of Things) requirements.

image

  1. Remote Monitoring  – Connect and monitor your devices to analyze untapped data and improve business outcomes by automating processes.  For ex: As a car  manufacturing company, provide an option to customer to remotely monitor their car condition, and suggest if they need a re-fuel or oil change.
  2. Connected Factory – Anticipate maintenance needs and avoid unscheduled downtime by connecting and monitoring your devices. For ex: As a car manufacturing  factory and spare parts are essential for car manufacturing. Automated solutions can ensure timely availability of necessary spare parts inventory to meet daily, weekly or monthly manufacturing needs.
  3. Predictive Maintenance – Connect and monitor your factory industrial devices for insights using OPC UA to drive operational productivity.  For ex: As a car service support, you can get near real-time performance data from the cars manufactured by your company, predict the health of each components in a car and offer timely maintenance to their cars.  Send real-time reminders and notifications to customers. Their by ensuring higher satisfaction levels for customers and more business value to the organization as it attracts more sales and good customer feedback.

image

These solutions will help you to:

  1. Connect and scale quickly – Use preconfigured solutions, and accelerate the development of your Internet of Things (IoT) solution.

  2. Analyze and process dataCollect previously untapped data from devices and sensors, and use built-in capabilities to visualize—and act on—that data.

  3. Integration and Digital TransformationEasily integrate with your systems and applications, including Salesforce, SAP, Oracle Database, and Microsoft Dynamics, making it simple to access your data and keep your disparate systems up to date.

  4. Enhanced security Set up individual identities and credentials for each of your connected devices—and help retain the confidentiality of both cloud-to-device and device-to-cloud messages.

Useful Links: