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What is Enterprise Data Governance?

Data is the new currency in today’s business climate, and data governance ensures that your company has a secure and organized system for managing this invaluable asset.

Corporate data governance is how an organization manages, analyzes, and leverages data to make business decisions. At its core, business-led data governance combines people, processes, and technology to create and execute standards that ensure data within an organization is accessible, usable, consistent, reliable, and secure.

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Good Data Governance


Key Takeaways:

  • Data governance combines people, processes, and technology to establish standards that ensure the accessibility, usability, accuracy, trustworthiness, and protection of data in a business.
  • Data management is the storing, maintaining, protecting, and analysis of data that functions under the policies and procedures dictated by data governance.
  • A data-driven enterprise’s policies and governance principles should ensure all company information is under control and used effectively.

What is a Data Governance Program?

A data governance program is one step toward digital transformation that combines people, processes, and technology. The primary goal is to guarantee reliable access to data so it can be effectively leveraged. To support these goals, the governance team manages user access and ensures that enterprise stakeholders have what they need when they need it. In addition, the goal of a control program is to protect from data loss, corruption, inaccuracies, and unauthorized access.


Related Content → What is Governance, Risk, and Compliance?


How Does Data Governance Fit into Data Management?

Data governance is a method for managing the roles, responsibilities, and processes of data assets, while data management is the operation concerned with the quality and accessibility of data. Data management includes the storing, maintaining, safeguarding, and analyzing of data that follows the policies and protocols put in place by governance. If data management comprises the tactics, then data governance encompasses the strategy. One comes before the other.


Related Content → Learn more about Data Management.


What are the Key Components of Data Governance?

People, Processes, and Technology

  • People
    It is critical to understand that data authority is not just IT’s domain. It should include people throughout an organization in the data management plan, including executives, IT professionals, and various other stakeholders within the enterprise familiar with relevant data structures. Having key people involved increases buy-in from end-users and increases the likelihood of leveraging the organization’s data. Organizations typically staff data managers and other IT pros to execute hands-on implementation. Some organizations include Chief Data Officers as part of their C-suite to play the lead advocate for their data governance program. Additionally, businesses will often create a committee with representatives from different areas of the organization. It is through this body that enterprise collaboration comes into play.
  • Process
    In data governance, the process is where the work happens. Thus, governance processes are the connective tissue within the practice of governance. From establishing, implementing, and evaluating policies and procedures to measuring and reporting, applying the governance protocol combines a series of careful steps designed to support the organization’s mission and goals.
  •  Technology
    Finally, if people are the who and process is the what, then technology is the how. Technology provides the tools and the infrastructure to support an organization’s data program by maintaining accessibility, security, reliability, quality, and more.

Good Data Governance Program Process


Why is a Good Data Governance Program Necessary?

  1. Improve Efficiencies, Reduce Costs, and Increase Revenue
    A primary goal of data governance is to eliminate data silos that can occur in an organization. When data silos build up, they can inhibit the flow of information and make sharing knowledge difficult. It is a collaborative process that recognizes the value of data. It aims to break down barriers by harmonizing data within an organization through the collaboration and coordination of enterprise data architecture implementation. Ideally, this process will lead to competitive advantages and increased revenue and profits.
  2. Increase Compliance and Reduce Risk
    Another goal is to ensure that data is compliant. That can be accomplished by creating uniform policies and procedures to monitor usage and include enforcement to eliminate risk from data loss and other issues. In addition, data governance can help to strike a balance between data collection practices and privacy mandates.

Data Governance Simplified

On the whole, data governance is the practice of securely managing data so an organization has the business intelligence needed to meet targets and fulfill business goals. A data-driven enterprise’s policies and governance principles should ensure all company information is under control and used effectively.

DOWNLOAD OUR GUIDEBest Practices for Enterprise Data Governance


Data Solutions

Coretelligent partners with a multitude of technology partners to provide next-gen cloud-based file sharing and collaboration. Building upon this foundation, Coretelligent adds its experience, know-how, and support to offer powerful controls for data management. Our approach allows your enterprise to maintain simplicity and usability for your workforce. Providing guidance and support is just part of what we at Coretelligent offer our clients.

Coretelligent’s solutions include IT planning, 24/7/365 support, cloud computing, cybersecurity, disaster recovery readiness, and more. Connect with us to learn how we can assist you with your data governance or other technology solutions.

Data Terms Data Lake vs Data Warehouse vs Data Fabric

Data Terms Data Lake vs Data Warehouse vs Data FabricOur shift to a digital world is fueling the creation of massive data reservoirs with almost unlimited potential. With this increase comes new data terms and technologies for managing and analyzing data. This digital transformation shift can result in companies generating more data than they can manage or utilize with their current infrastructure and resources if not adequately conceptualized.

Currently, we find ourselves firmly in the Zettabyte Era, a term coined back in 2016 recognizing the changeover to measuring the world’s data in terms of zettabytes. A zettabyte is a unit measurement for computing storage capacity, and it represents a whole lot of data. To provide some context, the world’s data is estimated to be just under 100 zettabytes in 2022. While in 1998, for comparison, the world’s data was estimated at just a few thousand petabytes. A zettabyte equals one million petabytes!

As digital transformation and the growth of data have become the norm, business executives must gain a broad understanding of the data landscape in order to take advantage of the business intelligence possibilities. Data management infrastructure can be complicated, and while there is no need for business leaders to become experts in data management, more knowledgeable leaders make better IT investment decisions.

Data Terms: Data Lake vs Data Warehouse vs Data Fabric

Gaining an awareness of data infrastructure terms like data lakes, data warehouses, and data fabric is a great place to start. A big picture overview of these data management technologies can only help in making more informed choices about your firm’s IT infrastructure.

What is a Data Lake?

A data lake is a centralized repository for storing enormous amounts of structured, semi-structured, and unstructured data. Data can be brought into a data lake from multiple and disparate data sources, validated, and optimized to improve access, connectivity, and analytics.

The main benefits of using a data lake are that it allows for cost-effective storage of large amounts of data without having to worry about the data’s format and can improve the functionality of data from multiple sources.

One pitfall of a data lake is that along with the unlimited data consolidation capabilities of the data lake, without the development of an adequate framework for enrichment and enhancement, data within a data lake is no more usable than before.

What is a Data Warehouse?

With a data warehouse data flows in from transactional systems, CRM, operational systems, and other sources, typically on a regular cadence. Business analysts, data engineers, data scientists, and decision-makers access the data through business intelligence tools and other analytics applications.

One key advantage of using a data warehouse is that it enables businesses to consolidate structured data from multiple sources into a single, centralized location to improve reporting and dashboards.

Having clearly defined and robust data governance policies is a requirement for getting the most out of a data warehouse.

What is Data Fabric?

Data fabric is a flexible data architecture that enables the integration of data from a variety of sources and cloud environments. In a sense, it knits together all the data of an organization regardless of the location or infrastructure providing a unified view of an organization’s data, making it easier for businesses to reduce data silos and better manage their data. Additionally, data fabric can help companies save money by reducing the need to duplicate data in multiple systems and providing flexible, agile, and scalable solutions for accessing and using data.

A Simplified View

Among the main differentiators among the three data structures is that data lakes can store raw data, while data warehouses only stores processed and refined data, and data fabric connects one or more of the other structures for better connectivity.

It’s About Business Intelligence

Data lakes, warehouses, and fabric are data technologies that can help businesses reduce silos and provide actionable data necessary in today’s data-driven business environment. Painting with a broad brush, they store (or can access) data in a centralized location, help businesses better understand their data, and reduce the need to duplicate data in multiple systems. Still, they have specific benefits and challenges that must be weighed against your organization’s requirements and business goals.

As with many things, there is no one-size-fits-all solution to data management and how best to gain the business intelligence (BI) needed to increase revenue, improve outcomes, and reduce the total cost of ownership.

Reach out to connect with our technical experts to discover how to optimize and utilize your data for better decision-making. Coretelligent has years of experience building and supporting customized IT infrastructure and solutions utilizing tools like Microsoft Azure, Power BI, Tableau, and other BI tools designed and built around our client’s business goals.

Are You Getting the Most Out of Your Data Governance Program?

Last month we shared the first in our series about the importance of having a data governance program. With this post, we go more in-depth about why data governance is the key to unlocking the power of your data to drive growth and avoid risk.

Are You Getting the Most Out of Your Data Governance Program?

What is a Data Governance Program?

Data is the new currency in today’s business climate, and data governance ensures that your company has an organized system for managing this invaluable asset. A data governance program combines people, processes, and technology to guarantee reliable access to data so it can be effectively leveraged. To learn more about data governance basics, read The Future of Analytics is in Data Governance: Are You Prepared?.

How Does Data Governance Fit into Data Management?

Where data governance is a program for managing the roles, responsibilities, and processes of data assets, data management is the operation concerned with the quality and accessibility of data. Data management oversees all aspects of data— storing, maintaining, protecting—but data governance provides the raison d’être. If data management comprises the tactics, then data governance encompasses the strategy. One comes before the other.


Related Content → Best Practices for Good Enterprise Data Governance Guide


Why is a Good Data Governance Program Necessary?

There are two main forces behind establishing good data governance in an enterprise.

1. Improve Efficiencies, Reduce Costs, and Increase Revenue

A primary goal of data governance is to eliminate data silos that can occur in an organization. When data silos build up, they can inhibit the flow of information and make sharing knowledge difficult. Data governance is a collaborative process that recognizes the value of data and aims to break down barriers by harmonizing data within an organization through collaboration and coordination with the implementation of enterprise data architecture. Ideally, that will lead to competitive advantages and increased revenue and profits.

2. Increase Compliance and Reduce Risk

Another data governance goal is to ensure that data is compliance appropriate. That can be accomplished by creating uniform policies and procedures to monitor usage and include enforcement to eliminate risk from data loss and other issues. In addition, data governance can help to strike a balance between data collection practices and privacy mandates.

Data Solutions with Coretelligent

Coretelligent works with a variety of technology partners to provide next-generation cloud-based file sharing and collaboration. Building upon this foundation, Coretelligent adds its experience and support to offer powerful controls for data management. Our approach combines an effortless solution with maximum usability, so your enterprise can focus on what’s important—growing revenue.

Providing guidance and support is just part of what we at Coretelligent offer our clients. Our solutions include IT planning, 24/7/365 support, cloud computing, cybersecurity, disaster recovery readiness, and more. Reach out to learn about any of our technology solutions.