With the proliferation of data sources and even more ways of collecting data, organizations have access to an unprecedented amount of data. Despite the wide availability of sophisticated data analytics tools and models, many organizations still struggle to bridge the gap between data collection and decision-making. The best data is that which is usable. In order to be usable, people need to be enabled to use it.

The disconnect between business users and data teams is not a new issue. There are several reasons why business users are often far removed from data teams, including:

• Technical complexity: Data analytics tools and technologies can be complex and require specialized skills to use effectively. Business users may not have the technical expertise or knowledge of data analytics tools to work directly with data teams.
• Lack of communication: Data teams may not communicate effectively with business users, leading to a lack of understanding about the data being collected and how it can be used to inform business decisions.
• Siloed data: Data may be stored in different systems or databases, making it difficult for business users to access and analyze the data they need.
• Time constraints: Business users may have limited time to devote to analyzing data, as they are focused on other responsibilities within the organization.
• Data curation concerns: Data teams may be reluctant to share sensitive or confidential data with business users, leading to a lack of trust and collaboration. In parallel, business users may often be overwhelmed by the raw volume of data shared with them if not appropriately curated for their specific use cases.
• Lack of data literacy: Business users may lack the skills and knowledge needed to understand and use data effectively. This can lead to a lack of trust in data, misinterpretation of data, and ineffective decision-making.
• All of the above and then some.

Rather than pointing to a single point of failure, the discrepancy between an organizations ability to collect data and its proficiency in applying it can be traced back to a deficiency in data enablement.

Data enablement consists of everything that contributes to turning your data into action. This includes making sure that your business stakeholders are able to easily access, use, and trust the data products designed to power their decisions. With good Data Enablement practices, even teams with the most archaic data stack can operate efficiently. On the flip side, even the most modern data stack can’t fix bad data enablement practices.

This problem is not solved with technology alone, but with people, process, and culture. Each of these components is essential to the success of a data enablement strategy.

Process

The process component of data enablement involves cataloging and documenting data to set up business stakeholders for success. This means creating a data catalog that provides a clear overview of all the data available, along with metadata such as data lineage, data quality, and data definitions. By documenting data in this way, business users can quickly and easily find the data they need and understand its context, ensuring that they can use it effectively to drive business outcomes.

People

The people component of data enablement involves onboarding teams across the organization onto data. This means creating a culture of data literacy that encourages all employees to work with data. Data teams can support this by providing training and education to business users on how to use data tools and techniques effectively. Additionally, data teams should work closely with business stakeholders to understand their specific data needs and provide tailored support as needed.

Technology

The technology component of data enablement covers the tools that help data teams manage these processes to support end data consumers. This includes data management platforms, analytics tools, and visualization tools that allow business users to work with data effectively. It also includes automation tools that can help streamline data management processes and make data more easily accessible to business users.

Enter the Data Enablement Lead

Silos are often created between different departments and data sources. The Data Enablement Lead is the primary liaison in creating an environment in which data can be easily accessed, analyzed, and used to make informed decisions. The Data Enablement Lead is involved in not only the processes of collecting data but also ensuring that it is clean, accurate, and relevant to the business. They are the stewards of a company’s single source of data truth and oversee the technology used to onboard both data practitioners and consumers onto data.

Why do you need a Data Enablement Lead?

When nobody owns a decision, it gets made by committee, and committees are notoriously bad decision-makers. As they say, a camel is a horse designed by a committee.

It’s not enough to just have data. Organizations that use data efficiently have a champion who is telling stakeholders how to use it, where to access it, and making sure that users trust it. It’s too common of a scenario where data teams create hundreds of reports and dashboards but the same questions keep being asked or the data is not being used.

A Data Enablement Lead is responsible for creating a data culture within the organization and ensuring that data is accessible to everyone who needs it. By having a Data Enablement Lead, businesses can ensure that they are maximizing the value of their data, making informed decisions, and driving growth.

Responsibilities of a Data Enablement Lead

A Data Enablement Lead  has several important responsibilities, including establishing data quality standards, auditing data to ensure that it meets those standards, and ensuring that the company is in compliance with all relevant data privacy regulations. They also work closely with stakeholders across the company to understand their data needs and ensure that the data is being used effectively to drive decision-making processes. Additionally, a Data Enablement Lead is responsible for ensuring that the data being used is consistently defined across all dashboards, reports, and business units.

The role of a Data Enablement Lead in a growing, data-driven company leveraging the modern data stack can be quite broad and may encompass a range of responsibilities. However, some of the most common responsibilities of a Data Enablement Lead may include:

1. Developing and implementing strategies for collecting, managing, analyzing, and utilizing data across various functions and departments within the company.
2. Leading data integration efforts, including identifying sources of data, designing data models, and developing data pipelines to ensure data accuracy and integrity for business decision making purposes.
3. Collaborating with cross-functional teams to identify data-related requirements and opportunities for innovation and automation.
4. Providing guidance and support to business analysts, data analysts, and data scientists in developing data-driven insights and solutions.
5. Overseeing the development and maintenance of data governance policies and procedures, including data security and privacy policies.
6. Creating and maintaining documentation for data management and governance processes, ensuring compliance with regulatory requirements and industry best practices.
7. Driving the development and implementation of data quality initiatives, including data cleaning, enrichment, and normalization efforts.
8. Leading efforts to supporting the adoption of business intelligence and analytics tools.
9. Providing thought leadership and expertise on emerging trends and best practices in data management, analytics, and business intelligence
10. Building a culture of data-driven decision-making within the organization

The lines are blurry. Some data enablement leaders focus on analyzing data, while others are skilled in writing production-level Python code but may not find it the most effective use of their time. What remains constant is the fact that they are focused on turning their company data into action and bringing new dimensions to how their company data is trusted.

Tools used by a Data Enablement Lead

There are several tools that a data enablement lead might use, including data visualization tools, data cataloging tools, and data management tools. Data visualization tools can help stakeholders across the company understand and analyze data more easily, while data cataloging tools can help ensure that data is organized, documented, and tagged properly. Data management tools can help ensure that the company's data is being used effectively and that it is properly secured.

Try Secoda for Free

Secoda is an ideal platform for data enablement leads looking to manage their company's data effectively. It offers a centralized location for all data sources, a simple and intuitive interface for data analysis, powerful data lineage tracking, and robust data governance capabilities.

As companies grow, they often end up with siloed data sources, making it challenging to gain insights from the data. With Secoda, all of your data sources are unified and can be accessed from a single platform. This consolidation of data allows for more accurate analysis and better decision-making.

Secoda provides a simple and intuitive interface that makes it easy for both business and data teams to work with data. Data analysts can explore the data in real-time, create custom visualizations, and easily share their findings with others. Additionally, Secoda's natural language processing capabilities allow users to query data in plain English, making it accessible to a broader audience.

Secoda provides powerful data lineage tracking capabilities. This feature allows data enablement leads to track the origin of data, ensuring data quality and accuracy.

With Secoda, data enablement leads can ensure that their data is secure, compliant, and governed by company-wide policies. This governance helps to mitigate the risks associated with data breaches, misuse, and regulatory non-compliance.