Microsoft Business Intelligence Case Studies

Microsoft Business Intelligence Case Studies-52
– Francisco Portugal, SPAR Administrator We managed to deliver and implement the proposed solution on time, and our Business Intelligence team’s dedication was full, so much that a strong connection between both companies persists to this day.

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SPAR’s sales grew by double digits in just a few months.

Dev Scope’s Power BI™ solution allowed the retailer to have a more detailed and informed view of their sales, prices, margins, and stock, and identify some key opportunities, such as products with a large profit margin but low in stock.

There is only one chance to make a great first impression so, after a brief Power Point presentation, we put words into action and took the liberty to connect a few of SPAR’s databases and extract some data previously deemed unreachable.

SPAR wanted to build a Reporting and Analytics (RAP) platform that could enable its end-users to be decision makers.

Learn why data science experts are using Python, R, Jupyter Notebook, Tableau, and Keras.

Berendsen plc and e BECS leverage the Microsoft Io T platform to gain Operational Efficiencies Business needs Publicly-quoted Berendsen plc provides textile services across 16 European countries, renting and laundering textile items such as workwear and hotel linen to a diverse and demanding range of customers.The company’s ultimate goal was to increase its teams’ efficiency but, in order to do so, they had to equip them with proper tools to not only analyze data but also act on it.Dev Scope’s proposed solution used Microsoft® Power BI™ to display data and was built on Azure Cloud Services, namely Azure Gateways and Service BUS to read and sync all business data stored in SPAR’s on-premise data sources.Dev Scope and Microsoft® Power BI™ have become an integral part of the management team at SPAR, and the company stopped depending on a SQL manager to extract data from queries.With the right data science tools, you can gain powerful insight out of the ever-growing pools of corporate data.Identifying which products’ sales were down during a given period could only be done if the server was updated daily and could take SPAR between 2 to 3 hours.After that, they would have to figure out where that scenario had the biggest impact, which could take an additional 3 hours.Yet the underlying challenge was a more subtle one, explains Berendsen’s IT director Duncan Macmillan—and one that tended to rule out conventional approaches such as barcoding.“At root, these are low-value, low volume items, which significantly impacts the cost-benefit equation,” he points out.As with most retailers of considerable size, SPAR collected massive amounts of data regarding their operation but accessing and crossing it wasn’t always an easy task.The retail sector can be ruthless to those unable to identify and grab opportunities, and SPAR had a huge need to analyze pretty much everything from suppliers to warehouses, sellers, marketing, finance, operations, etc.


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