Showing posts from 2019

IBI New Template - Excel Version

Hi everyone, The latest Excel template for IBI (Individual BI) is published.  Again, as usual this is a generic template which if you like to use you should customize to suit your needs.  The generic template is here - it has dates up to year 2030. It can be easily extended beyond 2030. To download, once you click on the above link, please click on the top right corner download button. To give you an idea of how to customize and use please see below a customized template that I created for my 11-year old nephew.   . And here you can find the customized template that I created for my 6-year old son  . All the best for those who are starting their IBI journey from 1st Jan 2020. IBI - Discover yourself factually. Update:  How to easily capture the data was already demonstra

Machine Learning with a simple example

Are you one among those who feels that everyone is talking about machine learning but no one seems to provide a simple example to easily understand it, if yes, this short video should help. And yes, you don't have to be a data scientist to use machine learning.

Discover yourself factually with IBI

Latest 2 minutes video on IBI provided below

1000 days of Individual BI

For those who have been following my IBI (Individual Business Intelligence or Individual BI) journey I am very happy to announce that I have completed more than 1000 days of data capture. On 15th November, 2019 I completed 1000 days. I had started capturing data from 19th Feb 2017. Based on the analysis of own data I have found some interesting patterns, learnt a lot about myself, stopped myself from doing the same mistakes again, noticed changes in patterns, etc. The benefits that I get from Individual BI are way too many. And therefore I will definitely continue IBI as long as I am able to do it. I will be happy to conduct a session based on demand. Let me know. Some of the charts are provided below to give you an idea of the possibilities with own data captured in a structured way consciously. Gaps in the above chart are because there was no weighing scale on those days or weight was not measured on those days. 

Before and Beyond Data Visualization

Presenting at EU DataViz 2019, Luxembourg on 12th November was such an honour. Thanks to the Publication Office of the European Union for the opportunity. It was a great experience both in listening to other inspiring speakers and also to present the topic of "Before and beyond data visualization". In my talk, I used two examples; Individual Business Intelligence (Individual BI or IBI) and PublicBI EUProc solutions to talk about before and beyond data visualization sections respectively. It was interesting to note that there were many people who were interested in the IBI example than I had expected, and some also had questions about data security. If any organizations (companies, colleges, etc,) would like me to present the topic of Individual BI at their premises I will be more than happy to do that.  My slides are attached below, if there are problems with the pages below, use this link -

Value of data

On 15th of November, 2019 I completed 1000 days of Individual Business Intelligence (Individual BI or IBI).  Everybody says data is an asset. I say, the data I have about myself is priceless. But, I was just wondering  if I were to estimate the price of the data I have collected over last 1000+ days, how much would it be worth? I have 104 data points (ideas, mistakes, dreams, health, work, happy days, etc.) captured for over 1000 days. Let's consider 1 EUR per data point.  So 104000 EUR Time spent in filling IBI data capture sheet everyday until now (1014 days) = 110.8 hours So around 11000 EUR (assuming 100 EUR per hour) Time spent in analyzing data until now (1014) = 76.5 hours So around 7600 EUR  So in total it is minimum worth 104K+ 11K+ 7.6K = 122600 EUR Would I sell my data? I don't think so. Would I share my data for a good cause? May be some of it.  I think if data is an asset, then we should also put a

How to protect the BI teams from doing non-BI work?

We often find ourselves in situations where the BI teams, because of the tools we use and skills we poses in dealing with data, are misused by other departments to carry out non-BI work. I would like to know how companies deal with these situations? Examples of non-BI work 1) Migrate data from old OLTP application to a new OLTP system 2) Create data extracts to be provided to other systems, example billing system or to be provided to B2B customers Because of the tight deadlines on the non-BI work these tasks get pushed on to the BI teams and the BI work is stalled. The non-BI task is also important but for the BI team it is a misfit.

EU DataViz Promotion

A number of interesting topics have been shortlisted to be presented at the EU DataViz 2019, Luxembourg. I have the honour to be one of the speakers. I will be speaking on the topic "Before and Beyond Data Visualization" Those interested please go ahead and register at

EU DataViz 2019

Happy to announce that I have been selected as one of the speakers in EU DataViz 2019.  Check the official page here - EU DataViz 2019 is an international conference organised by the Publications Office of the European Union. It addresses for the first time the specific needs of the community engaged in data visualisation for the public sector in Europe, bringing together experts, practitioners and solution seekers.

In-house BI Teams - Part 1 : Why you should consider joining an In-house BI team?

Are you tired of working as an external and researching for reasons to switch to an in-house BI team? Or are you in a situation where you have to choose between an IT consulting/services company position and an in-house BI team position for the next step in your career? Or just curious to know how it is to work in an in-house BI team? Irrespective of the reasons, I hope that the content in this part 1 of the in-house BI teams multi-part article provides you a well-rounded perspective about the topic and probably even triggers your interest to be a part of it. As there are various definitions for BI and confusions around it, it’s important that we clearly state what we mean by BI to ensure we are all on the same page before we start comparing how it is to work in an in-house BI team vs as an external. Business Intelligence In simple words BI (Business Intelligence) is all about deriving information and insight from data efficiently at scale to enable fact-based decision making in

2 years of IBI

It's been over 2 years that I have started IBI . A small subset of the results is shared below (charts) with an intention to create awareness about IBI. One of my personal objectives for this year is to create awareness about IBI among high school and university students.  So if any of you have connections with academic world and would like me to present the IBI concept, tools, my experience and learning from it, I would be glad to present. Almost everyone today, especially data professionals, preach that organizations should be data-driven, however, how many of the data professionals are themselves  data-driven individuals ? How many of us put in any effort in capturing and accumulating our own data in a way it can be used for self-discovery? Shouldn't we practice what we preach? We all agree that if we don't measure something, it can't be improved. Why don't we measure ourselves? Don't we want to improve? On 19th Feb 2019 I completed 2 years of capturi

Data, Information and Insight

What exactly does data, information and insight mean in the context of BI? Data : The raw form from which information and insight can be derived. Usually any recorded values, numbers, text, audio, video, stored in any form, any size and any location that gets generated in any event or transaction or just based on the current state or status.  It could be internal data like employee related data (name, address, phone number, gender, etc.) or products, services related data or customer related data or server logs, web clicks, call center data , product reviews, ratings, etc. Anything and everything that can be used to derive information is data. The much hyped big data is also data. It could be stored as files or in a database or just as logs. Burger Chain Example   For example, the event of a customer buying a burger from a fast food restaurant generates lot of data. Time of purchase, terminal used for payment, employee who served the customer, amount and currency of pu

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