Big data as an Economic Topic

There is an interesting conversation published by TechRepublic.  Big data is now an economic topic rather than just technology.  For applied science, it is far important to have real world applications rather than just on the paper or in the lab.   Please watch it and take Big Data into actions:

[Remarks:] Smart Data Institute Limited is a learning company sharing news and knowledge with the public for the promotion of value in technology applications.  Also, we do organize different training courses to different organizations and institutes.

Big Data - Economic Topic rather than Technical

What Data Scientists Really Do

There are lots of misunderstanding on the field – Data Science.  Unfortunately, there are lots of immoral businessmen stepping in and claims themselves data scientists.  It’s better to view the articles of Harvard Business Review with the sharing of data scientists worldwide.

For SDI team, we are focused in applying our data science experiences to help customer solving their business pain-points by insights.  In order to have the best-fit solutions, we are always working on industrial experts as a team like Financial Analyst, Accountant and Business Management Consultant.


How to Safeguard Your “Data Lake” for Better Decision Making

After a number of years with Big Data, more and more people are talking about Data Lake.  Hardware & software vendors are always happy to push boxes and big bills.  However, there is no myth and the lake is not just a collection of “water”.  The quality of the content within the data lake is the key of success.  Just like a lake, you should jump into water as not swimmable.

The editorial team of the “” use swimming to describe the concept of data lake application.  The article below is worth to read and understand the concepts before going ahead to the data lake.

Leverage AI without Losing Your Humanity

Automation, machine learning, machine vision, and natural language processing are all hot for corporations around the world.  Does it mean a replacement of jobs by machine?

Even we are data scientists, but we don’t want to see our solution is just a replacement of job.  These AI solutions should be supplementary to free up employee to do something else.  To take an example, a local bank in HK is using a ChatBot to alleviate the workload of customer service.  Customer service officers are focused on more customer centric services rather than general queries.  It is improving user experience without cutting head-count with limited investment in AI.

Let’s take a look on the article by the Editorial Team of

They have a number of info-graph to explain their idea.