Cracking Data Maturity Level 2: Standardization, Reporting & Automation

In our previous article, Data Maturity Roadmap, we discussed at a high level the different stages of data maturity. In this article, we will focus on practical steps to help your organization reach Level 2: Functional. This is an important stage, as it will completely transform your ability to leverage data to marvel customers and get modern operational habilities. At Level 2, your organization is no longer a combination of scattered data sources and spreadsheets. By following battle tested best practices, you will be able to create a system that can leverage exploit data to add real business value and scale to any future needs.

To achieve this, you'll need the right combination of ideas and tools. You need a high level strategy and a specific plan that is realistic and achievable.

In this guide we will give you a practical 3 step plan to get to Level 2 Data Maturity.

Data Maturity Level 2 Plan

The plan is divided into 3 steps.

Step 1: Planning & Design

The first step is to create a plan. We need to identify key data sources, define business metrics, and design a data model. We need to create a plan for data centralization, formatting, and automation. Finally, we need to define basic governance and disaster recovery policies.

You will need to create a data model of the key entities in your business and plan how data will flow from source to final reports.

Step 2: Data Centralization & Normalization

The second step is to centralize and unify data. We will feed all key data sources into a central repository and convert the data into formats that are the same across sources. To do this we need to automate data ingestion, formatting, enrichment and validation. Finally, we will create tables according to the designed data model.

In this step you will need to choose the right tools for data ingestion, storage, transformation and orchestration.

Step 3: Reporting, Automation & Security

Finally, on step 3 we will implement standard reports, dashboards, alerts and automation. This will allow us to monitor key business metrics and be alerted when critical thresholds are met. We can also implement predictive models to forecast future trends or use AI to deploy innovative solutions.

In this step you will need to choose the right tools for reporting, alerting, automation and security.