Microsoft BI Review

Very scalable and stable with a fluid interface

What is our primary use case?

We're a retail hospitality chain spread throughout India, operating over 330 outlets across the country in various formats, ranging from a coffee chain to fast food restaurants through our in-house bespoke brands. All these brands run out of travel hubs like airports, railway stations, and highways stops. We needed a solution to manage both the multiple SKU levels and in terms of individual dynamics, the profitability of each store. We constantly track the various types of back-end raw materials, specifically on our prediction modeling where we use Power BI. We also use Power BI analytics to drive those results with regard to the day-to-day dashboarding, reporting in terms of collection, on sales trends per hour, manpower and the like. We are customers of Microsoft and I'm the CIO. 

What is most valuable?

I like that the interface is very fluid in the sense that you can upload via Excel or you can attach via connectors, any software you like.

What needs improvement?

The challenge of this product is in truncating the table data. It would be great if Microsoft would include a naming convention which has the advantage of enabling a VLOOKUP on top of it, so two tables can be merged more seamlessly. Currently, the time it takes to merge two tables in Power BI makes the entire analysis quite complex because it requires common numbering in one table and then creating another common indicator in another table in order to merge the two. It wastes precious time. 

Secondly, while they talk about visual analytics, sometimes the challenge is when you're looking for more in terms of geovisual analytics, such as city maps which requires a functionality whereby you can upload transactions. For example, if I want to visually present my data on an airport map, showing which stores are generating what revenue dependent on the traffic heat map, I am unable to do that because I cannot upload drawings. Ideally, I'd like to show each store as a bar map with waves explaining the sales in each location. It allows me to pinpoint which locations are more profitable. 

I'd like to see a degree of variability so I have the flexibility of putting those variable components in my predictive modeling, and I can get a feel for the trends. It requires a common input database. You can do it in Excel, but you can't do it in Power BI, which I find surprising.

For how long have I used the solution?

We've been using this solution for nine months. 

What do I think about the stability of the solution?

The product is fairly stable, it doesn't get too many upgrades or updates from that perspective so it's fairly straightforward in terms of implementation and our entire ecosystem was on Microsoft which helped us. The only area that can be problematic is when you're trying to create relationships between two databases and you're trying to link it with your Power BI solution, sometimes that mapping takes considerable time.

What do I think about the scalability of the solution?

The solution is scalable. We are a cluster of eight legal entities and we've been able to expand to all of them. We started with 20 outlets and today we have 350 outlets. We are more granular and today Power BI allows us to drill down to the last voucher. We have around 14 users from the finance and operations teams.

How are customer service and technical support?

We haven't needed to call Microsoft, because we worked with one of their gold partners in India. So we are on an AMC model with them in terms of manpower. If there are any problems or upgrades we need, we reach out to the partner. 

How was the initial setup?

The initial setup was straightforward for the simple reason that our entire ecosystem was on Microsoft and we use Azure Web Services in terms of hosting. We split the entire project into two parts to simplify things. The first part was more about the granular analysis of sales and various other elements, which took considerable time due to the many external stakeholders involved. Phase two was relatively simple, because it was department specific and we created a split team, which led to the creation of a better platform.

What's my experience with pricing, setup cost, and licensing?

Licensing is on an annual basis. We have a complete Microsoft Ecosystem license. I think there is room for improvement with the licensing, specifically during the pandemic when it would have been reasonable to offer a discount. Many other companies, SAP and Oracle, for example, gave waivers to the MSME sector. Microsoft traditionally is used by smaller or medium-sized companies so I was expecting some sort of discount on the pricing, but unfortunately that didn't happen. We managed to avoid an escalation in cost, but frankly speaking, a discount would have been much appreciated.

What other advice do I have?

It's important to understand your entire ecosystem in terms of your tables; the kinds of tables your back-end database has and the elements of analysis that you are looking at. If you are looking at predictive modeling, you need to have at least two to three years of data, because that allows you to define the trajectory of the predictive modeling. Otherwise, it doesn't serve any purpose. Secondly, be very specific with your implementation partner, as to how you'd like a particular visualization tool to look, otherwise you may not get what you want. Finally, it's important to invest in people and create a center of excellence made up of people who know Power BI well, or who will get trained and certified on it. You'll need an in-house team which can do the small tweaks and changes as you require, otherwise you'll get stuck each time you need to do something.

I rate this solution an eight out of 10. 

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Microsoft Azure
**Disclosure: I am a real user, and this review is based on my own experience and opinions.
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