Today, in the era of modern sciences, massive amounts of data are produced and processed every day. The whole business is flooded with data from all angles and hence pressure is created to use the insights we glean from the data that has been processed. So building new technology that helps non-technical people to understand data, there is a desire and demand for Data Democratization. Let’s learn what that means with some strategies to right-size data democratization.
What Is Data Democratization?
Data democratization means democracy in terms of data. Making data accessible to everyone without any restrictions at the gateway of data. This enables non-technical users outside the IT department to own and extract value from enterprise master data. Decision-making and uncovering various opportunities are some of the core benefits of data democratization.
It is rightly said that “A company is as good as its employees.” Making your employees equipped with maximum features can save time and work for the betterment of the company.
The goal of data democratization is to have anybody use data at any time to make informed decisions with no barriers to access or understanding.
Strategizing Data Democratization
Knowing your data from root to leaf and answering all the questions that involve “What, Where and How” about your data is strategizing data democratization. A proper strategy includes all the processes leading from what data are you getting to who all can access what all information. 7 questions that organizations must ask themselves for creative a robust data democratization strategy –
Where is it coming from?
One of the biggest questions that we come across while working on data is “Where is it coming from?”. Knowing the source of data makes it more reliable and trustworthy as compared to knowing nothing about its whereabouts. Tracking the whole chain of data delivery helps us understand the data better.
With respect to democratization activity, different individuals or groups within your business will likely be looking to gain priority access to certain sources.
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What are we collecting?
The most important question that comes to mind when we talk of data is “What are we collecting?”. This means that we need to understand that what’s coming from those sources, means Data Accounting, and make a clear comprehension of the data.
You might be collecting a combination of contact data, response metrics, intelligence elements, or any kind of data to be worked on.
Where is it stored?
Now when we know that where our data is coming from and what it is, we need to understand “Where is it stored?”. This includes all the information like a Data Directory consisting of by whom it can be accessed and what all they can see.
You’re likely creating a data democratization framework to make it accessible to a non-technical team member to use and benefit from the information your business collects.
By knowing which data is stored where we can have a deeper knowledge of the whole model. This will help in planning who needs access to what data in a more elaborative functioning.
How do we control it?
After getting the data, the main concern is about its security. Data governance consists of data privacy, data ethics, and risks related to data democratization. These risks cannot be ignored, especially in a business environment where most of the employees can access the data that contains Personally Identifiable Information (PII) and some other information that may be considered ‘sensitive.
Because of all this, we need to control the shared data and govern it on a regular basis.
You need to come up with the right data governance strategy that enables us to gain full control over the data. All the information is not required by everyone. You can define who needs to see what data and you can also define the level of security, encryption, and other measures to control your data.
What maintains it?
As we talked about data governance, after it we have data management. For all the governance techniques we want to apply to our data, we need to maintain it as a whole and implement effective data management frameworks, processes, and tools.
Data quality, migration, transformation, and privacy are some of the main objectives of data management that can be achieved by deploying an effective data management strategy.
How to expand ownership?
To expand the ownership of data means to make data more and more accessible. Providing specific users with a specific amount of data to explore makes it more useful as it becomes more visible to that specific user.
This is why most businesses are providing their non-technical users the ability to work with data and generate the most profit out of it.