With growing e-commerce platform, business are becoming more data centric in terms of decision making, today we have a lot of platform which covers a wide span from traditional data storage [ Relational Model ] to Big Data [ Hadoop ].
With new platform coming into business the urgency for new data visualization has also increased, again the this domain has wide span to cover from legacy data visualization tools like Microstrategy, OBIEE, R SAS and now much talked about Power BI, which is surprisingly an eye catcher for every one in this domain.
There is no doubt excel has been far more productive especially in finance domain for any enterprise and to be very honest I am a die hard fan of excel, though we have state of art technology for data manipulation but still excel remains the first choice in many teams. So they why Folks in Redmond thought of building something new when they have excel. Lets analyze some of the basic shortcoming for excel.
Most of the time when we visualize data and try to find out some trend there standard time frame on which we want to see data, WoW known as vow [ Week over Week ], MTD, QTD and YTD adding to complexity we further break it down to CY and PY i.e Current year and Previous year. Considering any e-commerce business, the amount of data they generate in a single day ranges about 100,000 rows to 500,000 rows data [ considering all regions of operations], now here is the challenge with excel, processing such huge amount of data in excel has got major drawback
1) Slow processing
2) Non- Scalable when comes to slicing and dicing
3) Problem in doing a deep dive
4) Sharing the output and many more.
And that's how Power BI came into picture, no doubt it has the ability to process huge amount of data and has the capability to connect to any Data source makes it first choice of many excel users who are facing either one the problem outlined below. Sounds perfect ! but here was the hidden pain is.
Technically speaking you design a meta-data in Power BI to extract data and perform join at the back end, which is nothing but a traditional way of creating an ETL job or writing a SQL to obtain your desired result, considering 2 scenario, there are some added benefit with the second option, first you have lot more flexibility to improve the performance when you create an ETL job or write query, with Power BI there is a restriction. If there is a need to auto refresh your final output Power BI is slightly manual the second option is more flexible.
The most important feature as reporting analyst I want to is to drill up and down to see behavior at different granularity, Power BI kind of makes it complicated however especially with SQL you can easily do it. The deep dive feature in Power BI takes you to separate excel file when you try to go deeper, in SQL its pretty easy.
Bottom line if I have to spend so much of time and effort in creating one metric by collecting huge amount of data I would sit spend time in quality design so that I make a scalable reporting solution rather than use Power BI and make a one time use case.
Technology has got different perspective, what I think may be absolutely wrong to you and makes sense, however I would love to see feedback to know the opinion on the other side of the fence.
best
Siddharth Gupta
With new platform coming into business the urgency for new data visualization has also increased, again the this domain has wide span to cover from legacy data visualization tools like Microstrategy, OBIEE, R SAS and now much talked about Power BI, which is surprisingly an eye catcher for every one in this domain.
There is no doubt excel has been far more productive especially in finance domain for any enterprise and to be very honest I am a die hard fan of excel, though we have state of art technology for data manipulation but still excel remains the first choice in many teams. So they why Folks in Redmond thought of building something new when they have excel. Lets analyze some of the basic shortcoming for excel.
Most of the time when we visualize data and try to find out some trend there standard time frame on which we want to see data, WoW known as vow [ Week over Week ], MTD, QTD and YTD adding to complexity we further break it down to CY and PY i.e Current year and Previous year. Considering any e-commerce business, the amount of data they generate in a single day ranges about 100,000 rows to 500,000 rows data [ considering all regions of operations], now here is the challenge with excel, processing such huge amount of data in excel has got major drawback
1) Slow processing
2) Non- Scalable when comes to slicing and dicing
3) Problem in doing a deep dive
4) Sharing the output and many more.
And that's how Power BI came into picture, no doubt it has the ability to process huge amount of data and has the capability to connect to any Data source makes it first choice of many excel users who are facing either one the problem outlined below. Sounds perfect ! but here was the hidden pain is.
Technically speaking you design a meta-data in Power BI to extract data and perform join at the back end, which is nothing but a traditional way of creating an ETL job or writing a SQL to obtain your desired result, considering 2 scenario, there are some added benefit with the second option, first you have lot more flexibility to improve the performance when you create an ETL job or write query, with Power BI there is a restriction. If there is a need to auto refresh your final output Power BI is slightly manual the second option is more flexible.
The most important feature as reporting analyst I want to is to drill up and down to see behavior at different granularity, Power BI kind of makes it complicated however especially with SQL you can easily do it. The deep dive feature in Power BI takes you to separate excel file when you try to go deeper, in SQL its pretty easy.
Bottom line if I have to spend so much of time and effort in creating one metric by collecting huge amount of data I would sit spend time in quality design so that I make a scalable reporting solution rather than use Power BI and make a one time use case.
Technology has got different perspective, what I think may be absolutely wrong to you and makes sense, however I would love to see feedback to know the opinion on the other side of the fence.
best
Siddharth Gupta
