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Get the most of your key metrics with Business Intelligence - A step-by-step Technical Approach from start-to-end

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Get the most of your key metrics with Business Intelligence - A step-by-step Technical Approach from start-to-end

Business intelligence solutions give more power to C-level executives in understanding the scope of growth of their organisation by analysing the insights from their business, clients, and processes.

But for that, one needs a well-planned strategy or approach to get an advantage over competitors.

Start with creating a right business intelligence strategy that answers the following question: what is the objective, what resources do we have, and what resources are required?

You can decide on these questions by understanding at which stage your organisation is.

Take a reference from the above infographic. Next phase is to set KPIs which can vary according to the department.

For instance, KPI for a customer service department may be a net promoter score or customer effort score. But for retail, it's different and could be sell-through rate or sales per square foot.

Whatever it is, be sure about the metrics you want to track. Gather the right team that includes:

●    Business representative

●    BI Infrastructure architect

●    Data administrator

●    Application lead developer

●    ETL lead developer

●    Meta data administrator

●    Project manager

●    Subject matter expert

Now comes the tough part which is quite complicated to understand yet crucial for key decision makers.

The technical stack for the business intelligence implementation is very vast and depends on the type of tools you are using. For this, you need to follow the stages as shown in the figure

1. Choose the right data sources

Data is king here and you should know where it comes from. The source can actually make a big difference in getting the final answers for your business.

For instance, internal data sources like a company's records and archives won't make sense for a marketing team. Social media analytics, online surveys, feedback data, and Google data would be useful for them.

2. Capture the data

Identifying the right data source is not only enough. You need to ingest or capture data, again it depends on how fast you need the process to happen.

Data ingestion can be real-time or batch-based or both. ADF Azure Data Factory and Snaplogic are some tools to collect, extract, and load data.

With ADF Azure Data Factory and Snaplogic, you can also maintain the data flow easily and add custom data connectors. To deploy these, follow below steps:

1. Build the Azure resource group and then set up ADF Azure Data Factory.  

2. Once the ADF Azure Data Factory is setup, it's time to set up the Linked Service (LS). It is essentially a connection string to the data that has to be processed together with the runtime that is to be used for the Linked Service.

3. Create input and output datasets and create a pipeline with the Copy activity.  

4. Validate the pipeline and trigger the pipeline manually or automatically.

3.  Data Integration and Creating Warehouse

The data collected in the above step is not meaningful unless you process it and translate the data into a usable form. understand business intelligence concepts - data integration is thus the next important step in implementing business intelligence. It involves cleaning, transforming, and analysing data from the basic form to something meaningful.

There are two popular techniques for that, first one allows transformation of data before storing it into data warehouse with the help of Data flow.

Second one transforms the data at the destination end. In case of ADF Azure Data Factory, transformation happens at the end where database build tool uses SQL command on serverless data warehouse for data transformation.

For data storage, Google cloud platform and Amazon warehouse services are the two preferred choices among enterprises. Both are winner in their own terms like AWS comes with more service options where GCP is faster and cheaper.

4. Data Visualisation and Reporting

The whole process doesn't make sense if you can't use the insights. Data visualization helps you achieve it through graphics, dashboards, charts, diagrams, and maps. Power BI and Tableau are the most used data visualization tools to interact with key metrics and gain meaningful insights from it.

This would be the end result irrespective of the BI tool you choose. Let say, you picked power BI, now you can create custom dashboards, include graphics, and add filters. Here is how to get started.

●    Get Power BI pro, although youcan use the free version too. But the pro version allows you to use more dataand get accurate customer insights.

●    Allow the tool to extract datafrom data warehouse

●    Generate custom reports byselecting the important metrics

●    Go to Power BI homepage andmake a new dashboard

●    Choose reports from thehomepage and edit as per your need

●    Once you get the visual report,add more dashboard option. Edit if required.

You can either publish or share the dashboard directly from the tool. Now, all that you need to make decisions is right in your hand. Track the data daily or weekly or annually to understand the changes in your business process.


Business intelligence is as important as your customers and almost every business should rely on this to track their KPIs. However, one has to be sure about the goals they wish to achieve and choose right tools to create a useful data pipeline to implement the BI.

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