Creating a Connected Data Ecosystem

Data is a critical asset for businesses but without a connected data ecosystem, many organizations are missing opportunities to draw practical insight out their data. That’s because their day-to-day operational data is spread across the business, and they can’t supplement that data with the right third-party information. The pressure today is about more than looking back at reports about what has happened; it’s about using operating data to see the ups and downs coming sooner to be able to react—not only faster but also more effectively. Data can’t be used effectively to do this until it’s captured, cleaned, organized, and stored in a connected data ecosystem.

Whether you’re a business leader wanting to trust your data to make better decisions in the moment, a business analyst doing deep analysis to improve processes and systems, or a customer expecting up-to-date information, it’s essential to understand the elements that make up your organization's data ecosystem.

What Is Connected Data?

Connected data is data that’s integrated from multiple sources and linked together for use in analytics and other decision-making processes. The concept also applies to connecting operational data across distributed IT applications and platforms to improve processes and behaviors. Businesses can use connected data to gain a more complete and accurate picture of overall business performance or just one specific process within a business. Connected data also can help to increase process efficiencies and drive better outcomes because it enables businesses to establish a holistic view of operations and spot trends that otherwise may be missed. By contrast, operational data that is not connected causes frustration and delays in decision-making. For analytical data, business decision makers suffer from their inability to correlate and capture context and then make the right timely decisions.

What Is a Connected Data Ecosystem?

A connected data ecosystem is an environment that combines data from disparate business systems and provides a platform of data management and applications to support informed decision-making. Connected data ecosystems exist for the purpose of capturing all the data needed—and only the data needed—to produce useful and actionable insights or drive improvements in the effectiveness of a business’s people, processes, and applications. These ecosystems are designed to let organizations uncover value from their operational data by making it accessible, usable, and easily analyzed. By having a connected data ecosystem in place, organizations can clear the obstacles that keep employees from using data to quickly understand a disruption in the business—be it a sales surge, raw material shortage, spike in emergency room visits, or drop in interest rates—and to react in the best possible way.

Connected data ecosystems are comprised of computing infrastructure, business applications, data management tools and platforms, data integration and orchestration tools, data warehousing and analytics systems, data governance processes and tools, and data security and privacy systems. Artificial intelligence and machine learning tools are increasingly a part of this ecosystem, using algorithms to parse through masses of operating data and look for connections that might otherwise be missed. Like ecosystems in the natural world, data ecosystems are designed to evolve over time to meet the changing demands of an organization.

What Is a Connected Data Ecosystem?

• Infrastructure: Data captured, collected, organized
• Analytics: Search and summarized the data
• Applications: Feed relevant data into the ecosystem

Key Takeaways

• Connected data ecosystems are used by businesses to gather, store, analyze, and—most importantly—act on data from diverse sources.
• In a connected data ecosystem, operating data is blended together from all the sources necessary to help businesses foresee potential problems before they arise.
• Companies can use data ecosystems to better understand their business, improve processes, and make more informed and timely operational decisions.

Connected Data Ecosystem Explained

Connected data is the concept of linking together data from any data source and processing it to facilitate more efficient and responsive business operations. A connected data ecosystem takes this concept a step further, establishing a network of data elements that are joined to each other in a way that allows for more meaningful analysis and understanding. In a connected data ecosystem, data elements are linked together through relationships, thus providing insight into the overall data set. The purpose of a connected data ecosystem is to provide a comprehensive view of data for more effective analysis.

This connected data ecosystem relies on a technology platform made up of four broad parts: applications that run business processes in a company; data management infrastructure that processes and stores that data; integration tools that pull data in from all the disparate, relevant sources; and analytics engines, including AI capabilities in some cases, that help people make sense of all this data.

Connected data ecosystems contain data from various sources, which can include company-owned assets, such as databases, data warehouses, and spreadsheets, or third-party sources connected via APIs. The data in an ecosystem is organized in a way that allows it to be easily accessed and shared across different systems and applications. Key to a connected data ecosystem are the links between the data elements, which enable users to explore the relationships across the data set for relevant insights.

Importance of Connected Data Ecosystems in Business

A connected data ecosystem is an important tool for businesses looking to improve decision-making, increase employee efficiency, enhance data security, and foster collaboration. A connected ecosystem combines and transforms relevant data so that it can be analyzed and interpreted to inform business decisions. For example, if you’re a consumer goods company planning inventory levels, you likely need data integrated from myriad systems—forecast and budgeting, manufacturing, supply chain, HR, marketing, and sales. And here’s the key element: This isn’t a one-and-done annual or quarterly reporting job. Leaders responsible for inventory lean on this data ecosystem to stay on top of inventory as business conditions change, blending this ongoing operating data to anticipate trouble spots before they blow up. Businesses that use connected data ecosystems are more sensitive to change as it happens and therefore can make better decisions based on a more complete understanding of their data.

Connected data ecosystems can also better position a business to quickly respond to changing needs and opportunities via access to timely and targeted data. For instance, a global manufacturing company could use a connected data ecosystem to share and unify its data across its engineering, supply chain, and production teams for more effective collaboration, such as knowing when a design choice creates a sourcing or manufacturing headache. Likewise, a logistics company could leverage a connected data ecosystem to reduce costs by automating elements of shipment tracking.

Benefits of a Connected Data System

By tapping into the value of connected data, organizations can improve their overall performance and drive better business outcomes. Data ecosystems also can help employees find ways to generate new revenues, save costs, increase productivity, and improve customer service.

Key benefits of a connected data ecosystem include:

1. Improved data quality and accuracy: Connected data ecosystems allow for faster and more thorough data validation and reconciliation, resulting in more accurate and reliable data. When connected data is validated, enriched, and curated, it becomes trusted; and trusted data is what powers decisions and increases operational responsiveness.
2. Higher operational efficiency: With a connected data ecosystem, processes can be automated to reduce manual effort and errors and enable faster decision-making. Plus, employees spend less time hunting for data.
3. Better decision-making: A connected data ecosystem lets organizations access and analyze large quantities of data from various sources, helping leaders to make more informed, data-driven decisions.
4. Increased agility: By making complete and accurate data available more quickly, connected data ecosystems help organizations understand when business needs are changing, providing a more timely opportunity to respond with the right actions.
5. Stronger collaboration: A connected data ecosystem improves collaboration through easier data sharing across departments and teams, leading to better cross-functional communication and alignment.
6. Increased cost savings: Connected data ecosystems can lead to cost savings by reducing manual effort to find and assess data, automating processes to make them more efficient, and avoiding data errors and duplication.
7. More satisfied customers: Organizations with a connected data ecosystem better understand their customers and deliver more timely and personalized experiences, which leads to increased satisfaction and loyalty.

Components of a Connected Data Ecosystem

A connected data ecosystem is a technology stack with three fundamental elements: infrastructure, analytics, and applications, plus the integration to pull them all together. These components work together to create the ecosystem, enabling data to be captured and used for insights.

• Infrastructure: The infrastructure is where data is captured, collected, and organized by networks, hardware, and software. Storage, servers, databases, security and privacy services, and development tools are all part of the infrastructure, which increasingly is delivered as cloud-based services.
• Analytics: Analytics platforms search and summarize the data contained inside the infrastructure and connect various elements so that data can be viewed as if it all existed in a single location. Elements can include business intelligence visualization tools, machine learning algorithms, and statistical analysis tools.
• Applications: Applications, such as various types of performance management software, are the systems of record and systems of engagement that capture data and publish it to the ecosystem.
• Integration: Integration services are used to connect applications and data sources that enable process automation and data management.

Creating a Connected Data Ecosystem

Creating a connected data ecosystem involves collecting and integrating data, modeling the relationships between the data elements, and linking the data elements together to glean meaningful insights through analysis. Key steps to create a connected data ecosystem include:

1. Collection: Start by collecting the data that you want to connect. This could be data from various sources, such as databases, applications, or spreadsheets. This doesn’t necessarily mean putting all the data in a single location; it’s about understanding the data you have and need.
2. Cleaning: Clean data with data preparation pipelines. Standardizing data elements, transforming the layouts, enriching data, and removing duplicate records produces higher quality data.
3. Modeling: Establish the relationships between the data elements by creating a data model that defines the structure of the data and the relationships between the data elements.
4. Integration: Integrate the different data sources into a single connected data ecosystem. This could involve copying the data into a single database using APIs to retrieve data from various sources, using data integration tools to automate the process, or using presentation layers that hide from business users the complexity of all the data sources involved.
5. Analytics: Perform data analytics on the connected data to gain insights into the overall data set. Analysis could include activity such as querying data, generating reports, or building predictive models.
6. Governance: Establish policies, processes, and technologies to manage the security, lineage, quality, and accessibility of data within the ecosystem.

Harness the Power of Connected Data with Oracle

Connected data ecosystems are becoming increasingly important for businesses and organizations to make strategic decisions and respond to fast-changing business conditions. Understanding and engaging with an organization's data ecosystem leads to informed decision-making at all levels, resulting in a host of other potential benefits, including increased efficiency, more satisfied customers, and reduced costs.

When a company is building a connected data ecosystem, the team needs the right infrastructure and systems to support its operation. A data ecosystem can’t deliver without ensuring secure and reliable access to data. With Oracle Cloud Infrastructure integration services, businesses can extract, transform, and load data for data science and analytics and create code-free data flows into data lakes and data marts. The Oracle Integration product portfolio offers a complete collection of data integration tools and application integration services to help automate processes and centralize data management in the cloud. Oracle can help your business connect nearly any data store, process, application, service, or API across cloud and on-premises systems with Oracle Integration’s advanced solutions.

Connected Data Ecosystem FAQs

What is in a data ecosystem?

A data ecosystem is comprised of infrastructure, analytics, and applications that enable data to be captured and used for insights.

What is a data processing ecosystem?

A data processing ecosystem refers to the interconnected relationships between the elements or components that process data.

Why do businesses need a connected data ecosystem?

A connected data ecosystem gives a business a more comprehensive view of data for more effective analysis. Without it, businesses can miss opportunities to grow revenue, cut costs, or help employees be more productive.