Data Lake
About this topic
A data lake is a concept consisting of a collection of storage instances of various data assets. These assets are stored in a near-exact, or even exact, copy of the source format and are in addition to the originating data stores.
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We use Microsoft PowerBI extensively at the company. Over 15,000 reports.
For our "corporate" reports, like financials or HR, we centralize those requests and attend them with my team.
We currently "extract" information from multiple systems (ie. SAP, SuccessFactors, CRM, etc...) and put in into a SQL Analysis Services. For interpreting the data we have a Semantics model in PBI.
The problem I see is we can't scale enough to comply with the reporting demands as the semantic model is "unique" and we end up having only one or two developers that can work at a time.
Anyone has an idea how to scale their PBI teams without having to redevelop the semantic model per report?
What are the standard Service level indicators used when creating SLA document for Data Engineering products? I assume indicators like when new data will be populated for data products (all the previous day business transaction will be available by 9am, all source transaction reflected with in 30 mins etc) and accuracy and quality would be important. Is there Industry standard Indicators used to represent data product SLA? It would be amazing someone could share what they are using.
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