Data Science Courses You Shouldn’t Miss Out Today

If you are thinking about starting your journey in the field of Data Science and struggling to find a place to start from or contemplating to recast your career into the exciting world of Data, then you should not be missing out on these well rated Data Science courses at Udemy today.

Udemy has put these highly rated courses on sale at $10 today only.  Use promotion code YOUR2016 at check out, if you see a different price.

Search for ‘Data Science’ from the search bar for a quick preview of all the Data Science courses that could appeal to you starting from Python, R, Hadoop, Tableau etc.



Two Solid Data Science Courses to Pursue in 2016


Achieve your New Year’s career and learning goals with these two solid Data Science courses from Udemy – now on Sale at $10.

Data Science A-Z™: Real-Life Data Science Exercises :

This course will give you a full overview of the Data Science journey. Upon completing this course you will know: 

  • How to clean and prepare your data for analysis
  • How to perform basic visualisation of your data
  • How to model your data
  • How to curve-fit your data And finally, how to present your findings and wow the audience

This highly 5 Star rated course is  extremely hands-on and incredibly practical.

Learning Python for Data Analysis and Visualization

Through this course, you’ll get a full understanding of how to program with Python and how to use it in conjunction with scientific computing modules and libraries to analyze data. 

By the end of this course you will: 

  • Have an understanding of how to program in Python. 
  • Know how to create and manipulate arrays using numpy and Python. 
  • Know how to use pandas to create and analyze data sets. 
  • Know how to use matplotlib and seaborn libraries to create beautiful data visualization. 
  • Have an amazing portfolio of example python data analysis projects! 
  • Have an understanding of Machine Learning and SciKit Learn!

Both the below courses are on Sale at Udemy at a steeply discounted price of $10 (Promotion ends 01/11).  Jump start your learning goals today.

What’s in store for data analytics in 2015 and beyond

Future Gazing

Since the last couple of years, we have experienced revolutionary changes in the data analytics arena.  Big data became main stream and Data Scientist got termed as the sexiest job.  Data explosion has come with its own fair share of challenges and opportunities.  As the businesses are looking forward to monetize the data, they are grappling with finding suitable business use cases to leverage and execute on the new data platform.  Added to this is the trouble of finding skilled workforce to address the burgeoning demand.

Recent Alteryx research report has found that 72% of the business leaders are not satisfied with the speed at which insights are derived from data and nine out of ten dissatisfied stakeholders blame others on the inability to blend data from various data sources.

What to expect?

Segmentation of Vendors – Industry is fast gyrating towards three categories of vendors who are providing technologies that assist the data analytics life cycle viz. Data Platform providers like Cloudera, MapR, Hortonworks etc., Data Wranglers such as DataRPM, Tamr etc. and Guided Data Discovery providers like Alteryx, Datameer, Databricks etc.  Adding interesting twist to this mix is the new age big data visualization vendors like Platfora, Tableau etc.

It’s something of an irony if you find striking similarity to the data world where we used to live in until recently which was dominated by Oracle, DB2, MS SQL Server etc., as Data Storage providers, Informatica, Datastage, Abinitio etc., as ETL providers and Cognos, Business Objects etc., as the vendors for BI / visualization.

Few other distinct trends which we would emerge in days to come would be:

  • Machine Learning would become main stream
  • Deep learning could fast replace machine based learning technologies
  • Most of the predictive modeling and data science could become code-less or automated
  • Everyone would become data analyst or at least would be able to do sophisticated analysis through the power of these new found tool sets
  • Data blending would become main stream and rapidly get commoditized – a real threat to Big Data based analytics
  • Adoption of real time streaming and analytics would be higher – expect Apache Storm and Spark to be heard more often than before during your discussions
  • Signals based approach would become more prevalent than the atypical use case driven analytics approach where advanced analytics would be driven by a library of domain based signals.  We already see companies like Opera Solutions, Platfora, IBM’s Watson etc., taking lead in this space.
  • AI / VR could become an integral part of the strategy for the forward looking organizations
  • Graph databases would be increasingly used as the new destination repository for guided discovery / analytics
  • CIOs would have minimal say on the choice of analytics / tools / methodologies which would be driven by the business through the newly created roles like CDO (Chief Data / Digital Officers) or CAO (Chief Analytics Officers)

How many of these trends have you seen already kicking in?  Or have I missed out something more critical and significant?  What do you think?

Please share your thoughts.

Let’s ask bigger questions…

Image Credit – Morguefile

Free Big Data and Data Science Ebooks

A bunch of free Big Data and Data Science Ebooks which you should find useful.  You could download them for free using your Amazon Kindle.  If you don’t have a Kindle device, you could download it using a Kindle app for Android / iPhone / Mac / Windows.

I’d wish to keep this list active.  Do post your comments if you find any new Ebook that is free and covers either Data Science or Big Data.
Hope you enjoy reading them.


Big Data –

More than Big Data, it is the technologies that surrounds it and the hype around Big Data is baffling.

Nice info graphic of the Big Data’s 3Vs – Volume, Variety & Value. Velocity is something not covered surprisingly.

A quick and easy way to understand how big is this emerging space and it’s relative importance to the future.

While Big Data had its origin at Google and Yahoo, today Hadoop which is a key component of the Big Data framework has been well accepted in the enterprise.  This high adoption has increase the scope for new use cases.

Big Data

Big Data : Four New Books

With the flurry of activities and the noise being created around Big Data, it is but natural to see huge content getting generated around the subject.

Not to be left behind, the Subject Matter Experts (SME) have brought in four books on Big Data – three from the SMEs and one from the vendor IBM.

You could find them at Amazon.  Check out the links below and let’s know your views.  Happy reading !!


Summer Reading List : Ten Essential BIDW Books

Out on a summer vacation and still pondering about the projects? Well, it is time to catch up with some good summer reading books.

Presenting you with top ten books for your summer reading.  The list is based on what I would wish to or am in the process of reading. Hope you have your personal list too.

Would be more than happy to hear your comments. The list is not in any particular order :)

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Lean Integration: An Integration Factory Approach to Business Agility by David Lyle &  John G Schmidt

DQ and MDM with SQL Server 2008 R2

Data Quality and Master Data Management with Microsoft SQL Server 2008 R2 by Dejan Sarka & Davide Mauri.  Free Download.

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Building the Unstructured Data Warehouse by Bill Inmon & Krish Krishnan

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Agile Development & Business Goals by Bill Holtsnider, Tom Wheeler, George Stragand and Joe Gee

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Developing High Quality Data Models by Matthew West

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Data Architecture : From Zen to Reality by Charles Tupper

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Master Data Management and Customer Data Integration for a Global Enterprise by Alex Berson and Larry Dubov

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Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information by Danette McGilvray

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Business Intelligence Roadmap by Larissa T. Moss and Shaku Atre

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Competing on Analytics : The New Science of Winning by  Thomas H. Davenport and Jeanne G. Harris

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The Cloud Revolution: How Cloud Computing Is Transforming Business and Why You Can’t Afford to Be Left Behind by Charles Babcock


Mobile BI : For That Executive On-the-Go

Imagine a not very futuristic picture of an executive dressed in a matrix inspired black suit barking orders, which he lands at due to the business reports that some futuristic device presents to him.

With the changing face of business intelligence (BI), it’s no sci-fi fantasy that decision makers will have to simply keep dreaming about. The dream to have strategic business information in the palms of your hands is now within reach of the modern executives with the Mobile BI technology.

Evolving Mobile BI Landscape

The domain of BI has evolved significantly over the last few years. Several applications, now available, allow users to upload their own sheets and work thereon. Even Excel can provide great visualization using PowerPivot. Self-service BI has emerged as a popular model.

Simultaneously, the smart phone of today can offer visualizations, computing, and internet experience in addition to communication. Their rendition of graphics is close to laptops, thus making them ideal media for accessing BI reports.

Tablet PCs are another segment where mobile BI will see a lot of traction.

Mobile BI is meant for those highly mobile executives and who need to take decisions based on a few important KPIs (key performance indicators).  Other target segment of the user population could be the folks on the fields such as sales force, paramedics and for anyone who need data / information on-demand while operating from remote locations.

Limitations of Mobile BI

Although mobile BI has been gaining popularity, the technology has a few limitations. Listed below are some key short comings that mobile BI has today. This includes concerns about the amount of data that can be pushed to the mobile platform due to the limitations of the device in terms of viewable area, processing power, and memory.

  • Limited slicing and dicing: Mobile BI apps provide limited slicing and dicing of data owing to hardware limitations.
  • High Latency: For larger requests, the query returns to the server and configures the reports, thus increasing latency.
  • Associated Costs: Vendors providing their own apps also tie their mobile BI server to it, thus inflating the cost of mobile BI projects.
  • Real Estate : Another area is a problem akin to what the smart phone faces — the limited real estate/viewing area for data visualization and rendering.  However, tablets seem to have overcome this shortcoming.
  • Security : Amount and type of information to be sent to mobile devices and the kind of authentication to be built into the mobile platform are crucial challenges faced by CIOs and CISOs. A robust security and access control layer needs to be developed along with implementation of any enterprise mobility initiative, including mobile BI.  A combination of user authentication, mobile device security, multi-tier architecture, and data transmission security can help one mitigate the security risk greatly.

Mobile BI : What You Can Do

Organizations can implement mobile BI as a tool. Vendors like SAP BOQlikview, and Microstrategy provide mobile BI as an offering along with their BI suites.

Recently, Qlikview reverted to browser-based delivery of BI content thus moving away from native application-based delivery. This move could possibly have been driven by the proliferation of multiple device operating platforms such as iOS, Symbian, Android, etc.

The Open Source folks are not far behind. BIRT offers similar mobile BI (BIRT Mobile)functionalities which could be suitable for budget conscious but tech-savvy organizations. A new player, Yellowfin BI, offers embedded and social media BI capability. Two other players who have already taken the lead and worth watching in the mobile BI app market are RoamBI and PushBI.

On-the-Job Learning

The good part is that one does not need to hire a talented mobile developer in the IT team unless custom applications are to be developed. BI developers may utmost need to learn ways to nit-ti-grit-ties with the current desktop-based BI tools versus the mobile BI ones to implement mobile business intelligence.

The growing number of web conferences on Mobile BI offered through the leading vendors clearly heralds the level and impact this new delivery medium is bound to see in days to come.