If you have SQL Server database for a long time and you have database on the cloud also like SQL Azure or SQL Server RDS. You might want to understand how the data can help define, redefine, or build your business. Data driven decision or DDD for short is a way to make a business justification based on the data. DDD can be applied by using Business Intelligence platform such as SQL Server and Microsoft Power BI. SQL Server is used to collect, store, manage, and report the data insight. While Microsoft Power Bi helps you to design, develop, and visualize your data into a dashboard.
Power Bi or SQL Server BI
IF you have various data source THAN you can use Power BI (Premium version).
IF you have SQL Server data source THAN you can use SQL Server BI Platform
On this article, we will discuss the SQL Server BI Platform4
SQL Server BI Platform
SQL Server BI platform is Business Intelligence platform before the cloud era happens. What a good of SQL Server BI Platform is you can manage all of the BI process in your on-premises infrastructure. This is somewhat difference with Power BI premium that need Power BI services that should in the cloud. Beside of that. SQL server BI platform is a complete solution. You will have end-to-end BI service with SQL Server BI Platform. In contrast, Power BI doesn't manage the storage management or database engine except a storage that embedded in .pbix file.
Today you can run the SQL Server BI Platform workload in the cloud. For example, you can run the entire workload in VM or you can use data analytics managed services with Azure Synapse Analytics, Azure Analysis Services, and many more. Moving to cloud like Azure is a plus, because you can manage the grow of your data linearly and you don't need to manage underlaying infrastructure, patching, or updating.
If you start from scratch, I recommend you build your solution in the cloud. It is cost effective and easier to manage
Getting Started with BI Platform in On-Premises Environment
Imagine you have SQL Server database in your organization. How do you start your BI platform journey? What should you install? An how to setup the BI platform right away? You should understand what you need to install first. This documentation tell the BI component in SQL Server Install Business Intelligence Features - SQL Server | Microsoft Docs
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SQL Server Analysis Services. This service will help you to analysis the data in memory, in multidimensional storage, or in pivot model.
Data Quality Services. It will help you to measure, to perform data cleaning, and integration. This tool is included in Integration services.
Integration service. It will help you to do extract, transform, and load into your SQL Server
Master data services. It will help you to centralize and to improve consistency of your organization data. It will eliminate the redundancy and inconsistency of the data.
Reporting serves. It will help you to generate, render, and store the report for you database
How it Works
Let's make it simple by using a simple example. Imagine, you have lot of database that related with academic stuff such as student performance, library database, courses, lecturer, and many more.
Create the database just like what it should be with SQL Server
Use Master Data Service to find the understand the similar data in your databases.
Use data quality services to make sure the data in health state
Use integration services to integrate your database into data warehouse or big data
Use analysis service to analysis the result of integration services.
Use the reporting service to visualize and to create the report of the database
As a bonus you can use Power BI to create report and dashboard
Microsoft Offer in BI Platform
You can see the BI platform offer by Microsoft
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The Fun Fact about the data
When we build anything, we use data. Start from structured data, unstructured data, and semi-structured data we store the data to retrieve it as information and knowledge. Despite of the data usage, we know that the data in our life is growing. And when we can't store the data in the local storage the cloud is the answer. The question is how we store and manage the data in the cloud. This article will discuss how we store and analyze the data in the cloud era. You can read the data concept here
The Data Store
You can store the data in two types relational data or non-relational data.
In non-relational data you will have Azure Cosmos DB, File, Blob, and many more. You can learn more here
In relational data you will have the power of SQL Azure, as well as MySQL, Maria DB and any others database. You can learn more here.
If you need high volume transaction without than the Non-relational data is for you. However, for small and tight relation between data you need the relational database such as SQL Server. You can learn more the consideration here.
The Data Analytics
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After the data is stored, you can analyze the data for more useful manner. This step knowns as analytics. According to Microsoft they have several products which are?
Azure Data Factory who take any data and convert it into format that you need. The ETL process heavily happen in this Azure Data Factory
Azure Data Lake who store raw data to ready to retrieve as fast as it can. Azure Data Lake is the main storage for Azure Data Factory
Azure Databricks is a tool to provide big data processing, streaming, and machine learning. It can use data lake as a data source
Azure Synapse Analytics is an analytics engine. It is designed to process large amounts of data very quickly. Azure Synapse Analytics supports two computational models: SQL pools and Spark pools.
Azure Analysis Services enables you to build tabular models to support online analytical processing (OLAP) queries. You can combine data from multiple sources from the data lake, cosmos DB, and off course SQL Azure
Azure HDInsight is a big data processing tool based on well-known platform Hadoop.
You can learn more about analytics here. After you have analytics you can pull it into dashboard or report by using Power BI.
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I delivered Tech Talks event in 21 June 2019. The topic of the event is about Data Culture transformation. It is attended by 68 registered participants from university and IT professional. i discussed about three main topics
How Power BI shifts the data visualization for the end user
How data culture transformation helps the organization to get the insight from the data
How the organization improves their rapidness by using content pack, app workspace, and others
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you can see the slides here
Power bi data culture from Ridi Fe