Doing sound business decisions it's easier when your business only has 50 to 70 employees and a few projects. A small staff means you can keep in good touch with everyone and staying informed doesn't take much effort. A small portfolio of projects means you have full control over what's happening on each project.

This changes after the company grows. You need more data to make informed decisions, and that information is often scattered across several disparate systems. HR has silos, IT has silos, marketing has silos, PMO has silos, etc.

To achieve the sacred goal of data-driven decision making at scale, you need to build a data ecosystem that breaks down these silos. Centralizing and standardizing data from all these sources gives you a holistic view that improves data analysis.

This omniscience gives you the power to make decisions backed by concrete evidence, reducing risk and leading to more strategic and accurate choices.

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The value of a data ecosystem

If you've been hesitant to commit to building a data warehouse, that's understandable. It can be a significant investment of time, resources and budget.

You know there is value in it, but you may not understand the full extent of that value. From my perspective, these are the core benefits of building a data ecosystem, which directly helps build a strong organization:

• Improved customer understanding: A data ecosystem allows you to collect and analyze customer data from various touchpoints. This data provides a deeper understanding of customer behavior, preferences and needs. You can then leverage these insights to personalize marketing campaigns, develop targeted products and services, and improve customer satisfaction.
• Increasing efficiency and productivity: An AI-driven data infrastructure streamlines processes by automating tasks and eliminating manual data collection and analysis. Employees who previously handled these tasks are freed up to focus on higher-level activities.
• Innovation and Growth: Data repositories drive innovation by providing a platform for collaboration and knowledge sharing. By accessing diverse data sets and insights from other participants, you can identify new opportunities, develop data-driven products and services, and improve your business' competitive advantage.
• Risk management: improve data analysis helps proactively identify and mitigate risks by providing a broader view of market trends, customer sentiment and potential disruptions. This gives you the opportunity to address risks and develop contingency plans.

To build a scalable data ecosystem that delivers these benefits, focus on the following five key areas.

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1. Centralize data for accessibility

When you build a puzzle, you first throw all the pieces on the table and turn them face up. Then you can start analyzing them to find the edges, fit the pieces together and complete the puzzle to see the picture it creates.

You don't put all the skirt pieces in one cup, the blue pieces in another, the red pieces in a third, and so on. Why would you? This would make it harder to see how the pieces connect.

Likewise, keeping data in silos prevents you from seeing links. Centralizing your data improves it accessibility for stakeholdersreduces data silos and enables consistent data analysis across the organization.

To facilitate this level of comprehensive data access, collect and integrate data from various business operations (such as human resources, project management, and code repositories) into a data lake. You can use services like AWS, Google Cloud or Azure to create robust, secure and scalable data lakes.

2. Use technology for data integration

Once you have a centralized data store, you need a scalable process that maintains it timely and accurate data. You will quickly discover that the manual processes you have been using are not up to the task.

As more and more data floods into your business, automation becomes key. APIs and web hooks can automate the data ingestion and integration process, pulling data from disparate systems into your data lake.

3. Use advanced analytics tools

Visualizing and analyzing this tidal wave of data requires advanced business intelligence (BI) and analytics tools such as Tableau, Power BI or custom dashboards developed on platforms such as Shiny, Apache Superset or Dash.

These tools generate real-time insights and forecasts that support strategic decision-making. This may include analyzing project timelines, workforce productivity, or software development cycles.

4. Fostering a data-driven culture

Once you have the technology in place, the next step is to create one data-driven culture within your organization. Invest in training programs to increase data literacy among employees. Data literacy empowers team members to understand and use data effectively in their day-to-day decision-making processes.

Take steps to ensure broad access to data and analytics tools across the organization. This involvement encourages data-driven decisions at all levels.

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5. Maintain data governance and compliance

many law regulate the types of data you can collect, how it can be used and how it must be protected. Failure to comply with these laws can result in hefty fines, not to mention damage mitigation costs if you're hit with a data breach.

Develop and implement a data governance policy to protect your business and maintain the integrity and security of your data. This policy describes how your company uses and manages its data, who can access the data and how it can be used. It also establishes rules to help preserve data, defines the roles and responsibilities of data governance officers, and sets standards for data security and quality.

Your data governance officers should regularly review legal and regulatory requirements regarding data privacy and security, particularly in different geographic jurisdictions. Regulations vary and there are many to keep up with.

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Business, know yourself

You often hear entrepreneurs say, “We don't know what we don't know,” when talking about gaps in data collection. But when you have data in silos, it's more of a case of “We don't know what we know.” The information is there, but you just aren't able to put all the pieces of the puzzle on the table.

Focusing on these strategic areas, however, can help you build an effective data ecosystem that facilitates informed decision-making at the scale of your business. This leads to improved operational efficiency, improved strategic planning and a competitive advantage in the market.