From Raw Data to Insights: Steps to Achieve Data Democratization to Make Data Accessible and Secure
“Data democratization” has become a buzzword for a reason. Modern companies rely extensively on data to make informed decisions about their products, customers, strategy, and to evaluate the health of the business. But with an abundance of data, if your organization can’t leverage or access this data to make decisions, it’s not worth.
So, data democratization, or the process of making data accessible to all, is crucial to data-driven organizations.
Offering data access to all also implies that there are a few if any gatekeepers or bottlenecks who control this access. When stakeholders from disparate departments — like marketing, sales, finance, and operations — are incentivized and permitted to utilize this data to better improve and understand their business function, the whole company benefits.
Successful data democratization needs constant discipline and efforts. It’s founded on a company-wide cultural shift that allows a data-first approach and boosts every stakeholder to comfortably utilize data and make strong data-driven decisions.
In this blog, we will navigate through a detailed overview of data democratization, challenges, strategies and use cases. Let’s Dive in!
What is data democratization?
Born out of the needs to leverage sheer value out of Big Data, data democratization is a procedure that curates data accessible to everyone in a company without the requirement of heavy IT involvement.
With a robust data democratization strategy in place, every user in the company, regardless of their technical expertise, can have access to data for timely and more thoughtful decision-making.
This, in turn, assists analysts spend more time utilizing data and less time searching it. However, even when a company wants to empower all their employees with easy access to data, there can be numerous culture, infrastructures, and governance-related impediments to making data available easy to them.
What Business Challenges Does Data Democratization Address?
Organizations that democratize their data can address business challenges associated with:
Information access — Data democratization unlocks access to information previously confined in a data warehouse or data lake and accessible only by IT professionals.
Resource limitations — Data democratization alleviates pressure on valuable IT resources and frees them from having to fulfill data and reporting requests.
Data enablement — Data democratization allows organizations to get value from their vast data stores by empowering users to serve as their own data analysts or data scientists.
Major benefits of Data Democratization
Data democratization refers to the process of making data more accessible and usable to a wider range of people within an organization or community. The core benefits of data democratization are:
Improved decision-making: When data is more accessible to a wider range of people, decision-making becomes more informed and evidence-based. This leads to better decisions and improved outcomes.
Increased innovation: Data democratization can lead to increased innovation as more people have access to data and can explore new ideas and opportunities.
Improved collaboration: Data democratization can improve collaboration as more people have access to the same data and can work together to analyze and interpret it.
Increased transparency: Data democratization can lead to increased transparency as more people have access to the same data and can verify and validate information.
Better resource allocation: Data democratization can lead to better resource allocation as more people have access to data and can identify areas where resources should be directed.
Improved accountability: Data democratization can improve accountability as more people have access to data and can track performance and outcomes.
Overall, data democratization can lead to a more informed, innovative, and collaborative organization or community, with better decision-making, resource allocation, and accountability.
7 Steps to Right Sizing a Data Democratization Strategy
It’s important to right-size your data democratization strategy so that it is both effective and efficient. Here are seven steps to help you achieve this:
- Identify the scope of the project: Determine which data sets and analytics are relevant to the stakeholders involved in the project. Establish a project plan that details the scope, goals, and milestones of the project.
- Analyze the data: Review and evaluate the data to identify its quality, completeness, and accuracy. This step is crucial to ensure that the data is clean and trustworthy.
- Determine data accessibility: Determine the level of access each user group requires. This will help to ensure that the data is being used appropriately and that users have access to the data they require to do their jobs.
- Create user personas: Identify the user personas and their data requirements. This step helps to ensure that the right data is made accesible to the right people at the right time.
- Establish governance: Establish governance processes to ensure that the data is being used appropriately and is secure. Governance processes should include data quality control, data privacy, and data security.
- Provide training and support: Provide training and support to users to help them understand how to access and use the data. This step will help to ensure that users are using the data effectively and efficiently.
- Monitor and evaluate: Monitor and evaluate the effectiveness of the data democratization strategy. This step helps to identify areas for improvement and to ensure that the strategy is meeting the needs of stakeholders.
By following these steps, you can right-size your data democratization strategy and ensure that it is effective, efficient, and meeting the needs of your organization.
Top Data Democratization Use Cases in Various Industries
Data democratization is the procedure of making data more attainable to a wider range of users within an organization, so that they can analyze it and make data-driven decisions without needing specialized technical skills. This approach allows businesses to gain insights that can improve efficiency, innovation, and overall performance. Here are some use cases of data democratization in different industries:
Retail
In the retail industry, data democratization can help businesses understand customer behavior and preferences, which can be used to optimize pricing, promotions, inventory management, and store layouts. By democratizing data, retail employees at all levels can access real-time sales data, customer feedback, and other insights, without relying on IT specialists. For example, a store manager could access data on the most popular products, customer traffic patterns, and purchase histories to determine which products to stock and where to place them in the store. Similarly, a marketing team could access data on customer demographics, preferences, and purchase history to personalize promotions and marketing campaigns.
Finance
In the finance industry, data democratization can help organizations analyze large amounts of financial data and make better investment decisions. By giving more employees access to data, organizations can increase transparency, reduce silos, and improve decision-making. For example, a financial analyst could use data democratization to access real-time market data and financial reports to make informed investment decisions. Similarly, a risk manager could use data democratization to access information on risk factors and trends to manage financial risks more effectively.
Pharma
In the pharmaceutical industry, data democratization can help organizations streamline drug development and improve patient outcomes. By making data more accessible, researchers can collaborate more effectively, and identify new drug targets more efficiently. For example, scientists could use data democratization to access clinical trial data, patient records, and other medical data to identify new drug targets and develop more effective treatments. Similarly, clinical researchers could use data democratization to access data on patient outcomes and treatment efficacy to improve patient care.
Manufacturing
In the manufacturing industry, data democratization can help organizations optimize production, reduce costs, and improve product quality. By giving more employees access to data, organizations can gain real-time insights into production processes and identify areas for improvement. For example, a plant manager could use data democratization to access data on machine performance, energy usage, and production rates to optimize production and reduce costs. Similarly, a quality control engineer could use data democratization to access data on product defects and customer complaints to improve product quality.
Final Thoughts
Hence, data democratization is a valuable approach that can help businesses across different industries gain insights from their data, improve decision-making, and drive innovation.
By making data more accessible, businesses can empower employees at all levels to make data-driven decisions, collaborate more effectively, and drive growth.
