{"id":5974,"date":"2020-12-30T15:32:00","date_gmt":"2020-12-30T14:32:00","guid":{"rendered":"https:\/\/sodapl.com\/?p=5974"},"modified":"2022-10-24T08:30:31","modified_gmt":"2022-10-24T06:30:31","slug":"optimization-of-data-warehouses-and-power-bi-reports-for-the-retail-client-pronos-case-study","status":"publish","type":"post","link":"https:\/\/sodapl.com\/en\/optimization-of-data-warehouses-and-power-bi-reports-for-the-retail-client-pronos-case-study\/","title":{"rendered":"Optimization of Data Warehouses and Power BI Reports for the Retail Client \u2014 Pronos Case Study"},"content":{"rendered":"\t\t
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Pronos always focus on\u00a0quickly accessible and easily scalable solutions for our clients. For over four years we\u00a0work for the largest retailers in\u00a0Poland and not only. Our goal is to\u00a0provide them not only with the best possible solutions that will meet their requirements, but also allow them to\u00a0grow with our business partners.<\/p>\n

Therefore, we\u00a0successfully implement our solutions in\u00a0new companies, where we\u00a0use an agile approach not only in\u00a0project management but also in\u00a0our software. Thanks to\u00a0this, we\u00a0find the best balance between the technical requirements needed for proper operation and the costs that the customer always pays attention to.<\/p>\n

Since the beginning of our work, we\u00a0rely on\u00a0Microsoft cloud tools. That\u2019s why we\u00a0use a\u00a0variety of solutions from Azure every day to\u00a0develop our software. We\u00a0use them, among other things, as\u00a0a\u00a0storage space, an environment to\u00a0build microservices for our applications, space to\u00a0run VMs, data analytics environments, and more.<\/p>\n

As\u00a0the availability and capabilities of Azure services grow, we\u2019re not lagging behind. This is where projects like the one we\u00a0implemented for the leader of the retail in\u00a0Poland \u2014\u00a0optimization of Data Warehouses and Power BI\u00a0reports come from.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Problem<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The customer has been developing his data warehouse (DWH) for several years. The whole thing was previously embedded by\u00a0us on\u00a0Azure VMs, which provided us with stability, ease of scalability, and access to\u00a0the latest versions of the software. As\u00a0the business grew, the amount of data available for analysis increased. It was no\u00a0longer just sales data, but also full information about a\u00a0product, stock, inventory level, customers (and all about them), suppliers, etc.<\/p>\n

This amount of data increased every day and new reports came along with it. The use of virtual machines in\u00a0Microsoft cloud services made it easy to\u00a0upgrade available resources. This, however, caused the machines to\u00a0be\u00a0loaded during heavy tasks (e.g. running recurring reports, feeding data, \u2026) but almost unused for the rest of the day.<\/p>\n

Besides, it turned out that many of the business assumptions created at\u00a0the beginning of DWH are no\u00a0longer valid. The business has developed, new sales channels (e-commerce) have emerged. This has resulted in\u00a0the redundancy of data and measures in\u00a0reports. This again caused a\u00a0long waiting time for access to\u00a0key information.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Request<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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After several internal and external audits of the entire BI\u00a0ecosystem, which included a\u00a0review not only of DWH (data warehouses) but also of reports, the customer decided to\u00a0entrust Pronos with the optimization of the entire solution.<\/p>\n

Our task included:<\/p>\n

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  • reviewing and updating the data model in\u00a0MS SQL database and Analysis Services<\/li>\n
  • optimizing the data loading process (ETL)<\/li>\n
  • acceleration of tabular models<\/li>\n
  • improving the functioning of Power BI\u00a0reports<\/li>\n<\/ul>\n

    Also, the customer wanted to\u00a0optimize costs.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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    Solution<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    Our choice was to\u00a0introduce Azure Analysis Services (AAS), which was the transfer of tabular models to\u00a0typically cloud-based services. Besides, make the required changes to\u00a0the data warehouse itself and also in\u00a0reports.<\/p>\n

    We\u00a0began with reviewing the indicators required by\u00a0the business, the data available in\u00a0the DWH, and in\u00a0the source systems. From the analysis, it turned out that many conversions should have been done earlier \u2014\u00a0at\u00a0the data mart building level within SQL. This allowed us to\u00a0stop importing raw data into the \u201ccubes\u201d themselves. Many KPIs have also been transferred from Power BI\u00a0reports directly to\u00a0AAS models.<\/p>\n

    The analysis services that were used in\u00a0the \u201con-premise\u201d version have choked on\u00a0the amount of data and users. The transition to\u00a0Azure allowed us to\u00a0use tools to\u00a0manage them. Now we\u00a0can scale them \u201con the fly\u201d or\u00a0make the right amount of replicas for users. This allows the customer to\u00a0decide when more resources should be\u00a0made available to\u00a0operators (recurring report generation, daily analytics). The client can also decide at\u00a0what time the power is available for data load or\u00a0refresh.<\/p>\n

    The result of this project is to\u00a0expand structures with new resources, increase data availability for analysts and business users while keeping costs at\u00a0a\u00a0similar level.<\/p>\n

    End users noticed the biggest difference after implementing new Azure solutions. All reports they used before have accelerated significantly. In\u00a0some cases, the time to\u00a0access all data decreased by\u00a070%. Analysis of average times showed us that we\u00a0accelerated business by\u00a030%.<\/p>\n

    However, this is not the end of our challenges. We\u00a0have more changes ahead of us and a\u00a0full migration to\u00a0the cloud \u2014\u00a0Azure Synaptics, Data Lake, \u2026. At\u00a0the next opportunity, we\u00a0will talk about these changes.<\/p>\n

    ________________________________________________<\/p>\n

    Wojciech Pi\u0105tkowski, Head of Project Management, Pronos<\/em><\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

    Pronos always focus on\u00a0quickly accessible and easily scalable solutions for our clients. For over four years we\u00a0work for the largest retailers in\u00a0Poland and not only. Our goal is to\u00a0provide them not only with the best possible solutions that will meet their requirements, but also allow them to\u00a0grow with our business partners. Therefore, we\u00a0successfully implement our […]<\/p>\n","protected":false},"author":3,"featured_media":4438,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1,885],"tags":[],"class_list":["post-5974","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-case-study","category-soda"],"acf":[],"yoast_head":"\nOptimization of Data Warehouses and Power BI Reports for the Retail Client \u2014 Pronos Case Study - SoDA<\/title>\n<meta name=\"description\" content=\"Pronos always focus on\u00a0quickly accessible and easily scalable solutions for our clients. 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