Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. In the first Five worthy reads of this year, we’ll explore data democratization in detail, from its definition to its pros and cons, and provide some ways to use it for data empowerment.
Wouldn’t decision-makers want as much data as they can get before making a decision? No one wants to be blind during the decision-making process just because the right data isn’t available. This is what data democratization is all about. By definition, it provides end users who aren’t well-versed at handling data the means to access and analyze information, enabling faster decision-making. Since these citizen data scientists are not data professionals, they use self-service analytics, including visualization, reporting, and BI tools, to work with data.
Data democratization empowers business analysts and business intelligence professionals so they don’t have to constantly rely on data scientists, making the delivery of results easier and speeding up enterprise IT decision-making. It also enables non-technical workers to develop skills and share knowledge with others.
However, as every story has two sides, data democratization comes with its set of hurdles. The results delivered by non-technical employees may be less accurate due to their lack of data science knowledge. Even if non-technical employees know how to work with data, finding relevant data in siloed applications may take them so long that their data set’s integrity is compromised by the time they begin working with it.
Some of the ways to solve these challenges include developing and executing a data governance strategy to allow access to the right set of employees, and creating a comprehensive data catalog to help in further collaborative work.
Here are some interesting articles that talk about data democratization and the ways for your organization to approach this method.
1. What Is Data Democratization? A Super Simple Explanation And The Key Pros And Cons
Along with offering a competitive advantage, data democratization empowers employees by making them accountable for the actions taken post-analysis. It has the potential to be a game changer if the challenges like data integrity and duplication are solved.
2. What to Consider When Building Your Data Democratization Strategy
Developing a data democratization strategy brings up its own set of challenges, but implementing a biomodal strategy can solve some of these problems. A biomodal strategy involves exploiting the existing work of data scientists and experimenting with other methods to solve new problems. To increase the value of this strategy, organizations must work BI tools, master data management solutions, data warehousing, data security, and personnel training into their overall strategy.
3. 5 Best Practices to Help You Reap the Benefits of Data Democratization
To avoid succumbing to the impediments related to culture and data governance, business users who will be handling data must become proficient enough to understand their organization’s data ecosystem. This will not only enable them to free and use the legacy data through data integration systems, but will also help in transferring their knowledge to co-workers.
4. How and Why Your Enterprise Should Democratize Data Science
Yet another approach to follow while implementing a data democratization strategy is to start by identifying the business objective and domain of every data science project. This will help in suitably transforming the data that will be used in the machine learning models and getting a meaningful result.
5. Democratization of data? Start with a data-centric architecture
For a data democratization strategy to work, an organization’s data architecture must enable the smooth flow of data between applications. However, real-world problems, like use of legacy storage systems and the distributed storage of data in both on-premises and cloud applications, make it difficult to move data around. To overcome this, a hybrid cloud strategy should be put in place.
Although data democratization can open up ways for employees to work with data responsibly, it still has the potential to backfire if proper steps are not taken. With thorough analysis and continuous evaluation, data democratization can prove to be successful. If your organization has already begun working on this process, let us know in the comments section about the obstacles you faced, how they were solved, and the milestones you’ve achieved.
Credits: Illustration – Amirthalingam