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Showing posts from September, 2017

IBI in less than 10 minutes

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As promised to my friends, here is the shorter version of the IBI video
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IBI webinar video

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The IBI webinar video streamed live on 8th September, 2017 is here
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IBI webinar preparation and invite

How many ideas? How many of them materialized? How many happy days? How many dreams? and many more questions like these. Individual Business Intelligence (IBI) answers (or at least tries to answer) all of these with real data. In preparation for tomorrow's free webinar on IBI , I started carrying out some basic data analysis and visualization  on the  6+ months data (own and self accumulated data). While sharing of results is not required I have still shared it to give an idea about possibilities. Some results are published here in the IBI forum . Those interested to know more about IndividualBI please join the live webinar tomorrow (refer PublicBI for details on webinar ). Searching for full article about IBI?  see IBI
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IBI webinar invite

Posted in Linkedin ( Sep 2017) as part of the invite for the IBI webinar. Based on the current trend in #data accumulation and usage of data, it looks like the day is not far when 1) There will be state and central ministers for data like we have ministers for coal, petroleum etc.  Data is an important asset not just for commercial businesses but  for a nation too. Does any country already have this (not talking about statistics department)? 2) Companies  will be taxed based on the amount of data accumulated. And companies will add data in the assets column in the balance sheet. Any company already adds data as an asset in the balance sheet? 3) Rich kid or poor kid is determined by the amount of high quality data the kid inherits from his/her parents. 4) Self-reflection is done with consciously captured own data. For the first 2 points I have nothing more to add at the moment. If you are interested in the 3rd and 4th point then join my public web...
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Why big data is actually small?

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Posted an article with full details in Linkedin see Why big data is actually small? "Compared to the Universe anything and everything is very small" , wait I am definitely not going to use that line as a supporting point to present my point of view on why the so-called big data (#bigdata) is actually small. It's just a reminder of the fact that me, you, us, planet earth and this whole solar system is so tiny compared to the Universe and we shouldn't be making things look bigger than it really is . To say in other words we shouldn't be giving something more importance than it actually deserves. For those, who don't have the time (10 minutes) or patience to read the whole article, the reality and the gist is, big data is just a subset of data , a subset cannot be bigger or larger than the whole. No matter how big or large or complex big data is, it has to be smaller, less complex than data. Data is an asset , one of the most important asset in...
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ETL developer vs Data engineer

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Rephrased question : ETL developer vs Data engineer Answer : Unfortunately there are no strict industry standards on these job titles. That is just one part of it. Before ETL tools such as DataStage, Informatica, Ab Initio, etc., became popular, developers were hand coding every ETL flow. These ETL tools shortened the ETL flow development time to a great extent and allowed ETL developers to focus on business rule/logic/requirement (what to implement) than how to code it or optimize the code. There are many other benefits of using a tool but I won’t go into that in this answer. So an ETL developer with experience in these tools without any programming (coding) experience was/is able to design and develop end to end data flows. Whenever new types of source/target data format comes up, these tools catch up but it takes time, i.e., the ETL tool provider (e.g. Microsoft, IBM, etc.,) adds new components/connectors within the ETL tool to be able to work with new data format. For example, let’...
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KABI - The new Agile Methodology for BI Projects - Implement BI projects quicker happily

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KABI is a new agile software development methodology useful for achieving quicker implementation of Business Intelligence (BI) solutions. The methods defined in KABI can also be used in full or in part for any other non BI projects that share similar characteristics as BI development projects.  The word KABI is created by combining "KA" from KA nban and "BI" from B usiness I ntelligence. KABI is a lightweight, iterative, continuous feedback based agile software development methodology that enables every team member to work to their full potential even when there are several unknowns, resource constraints, dependencies and unpredictability of work load. Thereby KABI ensures optimal team productivity throughout the project duration. At the heart of KABI is " Peer Inspiration ".  Every team member plays an important role and every team member works in an exemplary way. They do their part of the job so well that it inspires the whole team. " Mutual...
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BI Architect course and BI Tool question

Received two questions, 1 through LinkedIn and other through blogger. Sharing details of Q&A here for the benefit of wider audience. Question 1:  I want to start with a career in BI, and I am planning to get trained in it. The institute covers MSSQL, Power BI, MSBI, Tableau desktop 10, Informatica developer and admin, Azure data factory, SQL DBA, QLIK sense, Data warehousing. Is this all that is needed? Reply : Regarding getting into BI, the best way is to get into a team where you can learn from experienced people in the team. Regarding courses, just based on the list, that's quite a lot for a training, but it depends on what exactly is provided as part of the training. Need more details about the training. Then once the link was provided, I had a check and provided below reply. Note - Link or institute name is not shared here intentionally to avoid any confusion that I am promoting any institutes.  Reply :   I have had a look into the link, as a cour...
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