How to implement business intelligence (BI) similar to healthcare BI? Implementing business intelligence involves a series of activities that enable your organization to use a BI solution. In this article, we discuss the steps you must take to achieve the maximum benefits of this technology.
Steps for Implementing a BI Project
- Gathering BI Requirements and Creating Resource and Funding Plans
Do you possess a comprehensive specification document for your new BI system? This document enables you to systematically evaluate your completed BI solution to ensure it aligns with your initial project objectives. Furthermore, it serves as the sole foundation for determining the requirements of your Resource and Funding Plan.
What specific queries should this specification document address?
- Who will be the users of the system?
- Which business processes, responsible for digitalization, do they oversee?
- What KPIs and metrics are necessary for tracking within your BI reporting system?
If you lack a detailed specification document for your new BI system, you might need the services of a BI Business Analyst who possesses a deep understanding of your business processes and can create this document for you. This analyst will chart out your enterprise’s business processes, outlining their interconnections. The document will include a comprehensive list of all the functions within your enterprise, along with their respective key stakeholders and associated KPIs and other performance metrics.
The resulting map serves as the basis for the specification and lays the groundwork for the future BI system. This framework enables the development of a role-based access model (determining which employees will have access to specific information) and provides executives with insights into the relationships between critical business parameters. The specification forms the foundation for a Resource and Funding Plan, providing essential information such as implementation steps, project timeline, and costs (including human resource involvement from both your team and contractors, as well as the project budget).
2. Design and Construct a Data Warehouse for Implementing Business Intelligence
The goal here is to combine various data sources (like Databases, Flat Files, Marketing Analytics, Social Media, CRM/ERP, Helpdesks, etc.) into a single unified source, known as a ‘Data Warehouse’ database or a set of databases.
Steps to Implementing a Data Warehouse
1. Design the Data Warehouse data storage structure, specifying which tables hold different types of data (physical data structure).
2. Create scripts for each data source to:
- a) Extract data from them.
- b) Verify data for duplicates and errors, transforming it to meet Data Warehouse requirements.
- c) Load the processed data into the Data Warehouse.
This step is known as ‘ETL processes configuration’ (ETL stands for ‘extract’, ‘transform’, and ‘load’).
3. Optimize the Data Warehouse for intricate calculations, a process known as ‘Data Enrichment configuration’.
Why is this necessary?
a) For tasks like ABC(XYZ)-analysis, categorization, forecasting, and modeling, resource-intensive calculations are required.
b) You may have experienced Excel freezing or crashing when handling complex metrics. One of the reasons is attempting to calculate intricate metrics in Excel, which is primarily a data visualization tool. Working with large data volumes or complex formulas worsens this issue.
Following best practices in BI development, it’s recommended to perform complex data calculations, including KPIs, at the database level (backend), not at the visualization tool level (frontend). That ensures that your business reports are fast and reliable.
3. Connect the Data Warehouse database with the OLAP Cube database.
Creating reports for your team based on Data Warehouse data typically involves manual database query writing by a developer. However, this approach is outdated for modern businesses. Instead, you can utilize another technology – an OLAP Cube database.
For instance, suppose you want to generate a multidimensional report. In your Data Warehouse, you have three tables: sales by date, sales by location, and sales by products. To obtain a report on a specific product’s sales at a particular shop on a certain date, a developer would need to write two queries to the Data Warehouse: one for sales on a specific date and another for sales at a particular shop. Plus, an additional query to consolidate the data. This process can be cumbersome even for a simple example.
But once the OLAP Cube is set up, you won’t require a programmer to create multidimensional reports. It only takes a standard Excel query to get one. The OLAP Cube handles the heavy lifting because it has the necessary data and dimensions like “date,” “shop,” and “product” for each sale.
4. Visualizing BI Data
The previous steps helped us create the databases and ensure data accuracy. Now, we focus on Dashboards, Scorecards, and Reports. This step provides the interfaces used daily by you and your team.
These interfaces come in three types: Dashboards with graphs, Scorecards, and Spreadsheet Reports.
Dashboards:
- They display high-level metrics, including real-time updates, for specific processes and the overall business.
- The goal is to provide a quick overview, not necessarily cause-and-effect relationships.
- Graphs are commonly used.
Scorecards
Scorecards are a type of dashboard that focuses on KPI performance, comparing it to planned results and highlighting deviations in separate processes or overall business.
Reports
Reports, on the other hand, are designed to uncover cause-and-effect relationships and provide structure within specific processes. This data is later summarized for dashboards.
Reports can be preconfigured or easily customized by users, allowing for self-service multidimensional reports without the need for analysts, data scientists, or IT specialists.
5. Deploying Business Intelligence
You can assess the complete picture only when all prior steps are done. Now, you’re sure that everything, both calculations and visualizations, performs quickly (within seconds) without burdening servers or user computers, avoiding costly equipment purchases.
That is the moment to determine the best refresh schedule for your dashboards and reports. For instance, real-time updates are necessary for IoT data (demanding higher hardware resources), but ABC-analysis data may suffice with monthly updates.
6. Configuring BI Security
1. You may want to specify who can access what information based on job roles (e.g., employees not needing access to co-workers’ salaries unless necessary for their duties). A contractor sets up role-based security, ensuring flexible control for adding/deleting users and assigning access rights.
2. The contractor establishes a Non-Disclosure Agreement (NDA) with you, legally safeguarding your data used during BI solution development and implementation.
7. Business Intelligence Training
When choosing an outsourced contractor, make sure they provide comprehensive and intensive training on system tuning and utilization to various user groups, such as data engineers, business analysts, and business users.
