Strategy to Data Pipeline Integration, Business Intelligence Project

Understanding Core Concepts:

In reality, data integration is just another word for integrating systems.

The main task of data integration is to secure the flow of data between different systems (for example an ERP system and a CRM system), each system dealing with the data with whatever business logic that is built into them.

Very often, data integration transfers operational data from one system to the other, for example: Customers, Contacts, Items, Quotes, Orders, Invoices or Sales history.

But the scope of data integration can also include other types of data, for example either traditional master data (such as posting groups and other metadata that secure a consistent system setup and reporting) or it can basically be any table or field that you choose to map between the different systems.

In reality, there are no limits to which data that can be relevant for data integration, it only depends on your system landscape and the business processes you are following.

HOW DO YOU SETUP AN ADVANCE DATA ARCHITECTURE & BUSINESS INTELLIGENCE PROJECT?

STEP 1: DEFINE YOUR BUSINESS PROCESSES AND DATA INTEGRATION SCOPE

To integrate, you need to understand what your processes actually are and what kind of integrations you’d benefit from.

For example, usually a customer in your ERP system will have come from your CRM system. They got into the CRM system by being converted by the CRM from a lead.

This would result in this data integration flow:

• Trigger event in the CRM system (such as first order)
• Customer created in ERP system.

STEP 2: CONNECT YOUR SYSTEMS VIA A DATA INTEGRATION PLATFORM

The two systems being integrated need to be connected. System designs (that is, tables, fields and other relevant information) are read and stored to allow data to be mapped.

STEP 3: SYNC YOUR SYSTEMS

Once testing and transfer is done, it’s time to sync your systems. This is usually best done in stages, making each area live as you go. This means you’ll start benefiting from integration more quickly.

When you’ve finished syncing and everything is working as it should, it’s time to switch to support mode. This is generally easy to manage with a data integration platform, which should send an email notification when something goes wrong, along with all the information they need to start fixing it.

WHAT IS BUSINESS INTELLIGENCE?

Let’s begin with a definition: business intelligence or BI is a set of practices of collecting, structuring, analyzing, and turning raw data into actionable business insights. BI considers methods and tools that transform unstructured data sets, compiling them into easy-to-grasp reports or information dashboards. The main purpose of BI is to provide actionable business insights and support data-driven decision making.

Phase 1. Configure a data warehouse and choose an architectural approach

Data Warehouse

Once you’ve configured data transmission from the chosen sources, now you have to set up a warehouse. In business intelligence, data warehouses are specific types of databases that usually store historical information in SQL formats. Warehouses are connected with data sources and ETL systems on one end and reporting tools or dashboard interfaces on the other. This allows for presenting data from various systems via a single interface.

Phase 2. Set up data integration tools

The integration phase of the actual tools will require a lot of time and work by your IT department. There are various structural elements of a BI architecture you will have to develop in case you want to create a custom solution for your business. In other cases, you are always free to choose a vendor from the market that would carry implementation and data structuring for you.

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