Chapter 1

8 Steps Towards a Modern Data Estate

Steps 1 - 4

#1 Define Your Goal in Terms of Data and Analytics Maturity

How mature is your organization in the area of data consumption? What do you want to achieve with your data estate in terms of analytics maturity? In the article ‘Take your Analytics Maturity to the Next Level’, Gartner cites that: “In a recent Gartner survey, 87.5% of respondents had low data and analytics maturity, falling into ‘basic’ or ‘opportunistic’ categories. Organizations at the basic level have business intelligence (BI) capabilities that are largely spreadsheet-based analyses and personal data extracts. Those in the opportunistic category have individual business units that pursue their own data and analytics initiatives as stand-alone projects, but there is no common structure across them.”

In this step, you ask yourself what is currently working and what is not working. You describe the bottlenecks, pain points, and data silos in your organization. At the end of this step, you have a clear understanding of what you want to achieve, which pain points you are going to solve, and where the low-hanging fruit can be found.

#2 Define the Business Needs of Today and the Future

“In a competitive environment, where data can make or break a business’s competitive advantage, corporate success might very well be measured by the maturity of its enterprise data program” mentions the earlier cited article from Forbes.

In this step, it’s not about IT. It’s not about limitations, restrictions, or data silos. It’s all about a laser focus on business requirements. When transforming your data warehouse into a modern data estate, the biggest mistake one can make is a replication of the existing environment into a new environment. You need to ask the right questions to every stakeholder involved, from sales to marketing and from HR to operations.

What do they want to measure? Where will their business be headed in the future? What trends do they see? How will digital transformation impact data insights? An HR leader wants to measure traditional KPIs today, such as employee engagement, diversity, or belonging. Trends in HR, such as the war on talent will however mean that HR needs insights into the individual skills and competencies of employees so that scarce skills can be quickly allocated to the most strategic projects.

Following your tour of the business, it’s time to prioritize these business needs, as you will want to start out small.

#3 Describe the Core Business and Data Processes

You’ve defined your goal in terms of data and analytics maturity. You’ve prioritized the business needs of all your stakeholders. Now it’s time to identify the data sources you have available – and which data you want to initially find a home in your data estate to respond to the highest priorities from your list from step 2. This step is both about business processes and data processes since they are connected. You look at a certain data point, such as customer data, and then you define the relational data models. How is this customer data is used in your business processes? The same applies to transactions, products, and more.

#4 How Will the Data be Accessed and by Whom?

Employees are different in the data they have access to (security) and in the way they access the data (tooling). In this step, you describe your security strategy and the tools for analyzing, reporting, and visualizing data. The first question to answer: How are you going to connect to the data sources? What connectors do you need? How often can you read data? What kind of data do you get? What metadata is available? How often is data updated and how often do you have access to data? The second question to answer is: how will you manage security and access rights?

How people access the data

Consider the data consumers you want to serve, and how you want to serve them. You want to provide self-service BI for different types of consumers, ranging from power users such as data scientists, data miners, and AI and ML algorithms to business users working ad-hoc with data and creating new reports, and casual users waiting for the routine reports and updated dashboards.

The data people can access

In this step you define roles and groups so that, building your data estate, you can identify users and access rights. This ensures that authenticated users only access the data, tables, or columns they are authorized to see.