Businesses are deluged with plentiful data and are under staunch push and in need of generating insights by making sense of that data. Data is truly a game-changer if allowed to go beyond a few teams and is extended to the masses.
The good part is that almost every employee can and should be data-aware and literate to process this data and enable the business to take critical decisions and grow. The data-driven transformation is now no more limited to the privileged data analyst or data scientists.
The Era of Data Democratization
Whenever we talk about data and its accessibility, one word that aptly describes the process is called data democratization.
In the words of Bernard Marr, the author of “Big Data in Practice”:
“Data democratization means that everybody has access to data and there are no gatekeepers that create a bottleneck at the gateway to the data. It requires that we accompany the access with an easy way for people to understand the data so that they can use it to expedite decision-making and uncover opportunities for an organization. The goal is to have anybody use data at any time to make decisions with no barriers to access or understanding.”
More so, there is an excellent and elaborate definition of data democratization that goes beyond just data accessibility:
“the ongoing process of enabling everybody in an organization, irrespective of their technical know-how, to work with data comfortably, to feel confident talking about it, and, as a result, make data-informed decisions and build customer experiences powered by data.”
True adoption of data democracy in an organization stands on three pillars:
Effective Data Democracy and its Need
Have you ever felt constrained by a lack of data? Does your organization support the employees to ask data-related questions and help them resolve their data needs? All the hidden patterns and meaningful actions that a business is in need of can be best achieved with only one tool - data.
The varying concerns of a data user primarily include not knowing what is the right dataset and the right tools to use to answer the business queries. Besides, the data users might also lack the necessary skills to solve the business problem by themselves and need support and assistance from the data experts. Lastly, they also struggle with whether they can trust the data to deliver mission-critical solutions.
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Effective data democracy facilitates the data available to the users with a single source of trusted view thereby breaking the data silos.
It is also synonymous with self-service analytics tools that allow business users the freedom to independently gather and analyze the data without any external support or dependence.
Think of the ease that comes with a data catalog that takes an inventory stock of all your data requirements and has a search engine in the backend that responds to your data needs and queries.
The employees might have varying understanding of the business problems and some of them are better equipped to answer the key concerning questions, if there are no gatekeepers, they can quickly access and pivot the analysis with respect to stakeholders’ requirements.
Expedited access implies timely analysis and quick results - this helps the data-literate organizations gain a competitive edge and optimally monetize their data.
Canonical understanding of data democratization and governance is presumably with the IT department. However, the dynamically changing landscape where the data is generated at an exponential rate indicates that IT is only a facilitator of the developers' need for business objectives. Primarily, the data requirements need to flow through the business in terms of what data is required and in what shape and format.
But what if all the users are not technically skilled enough to rightfully use the data and end up fabricating the bad results. While the appropriate use can accelerate an organization’s path to success, a bad analysis can impede trust and destroy the business strategies.
Most importantly, increased access to data poses security concerns and challenges in maintaining data integrity. Lastly, each team will have their own understanding of data that might or might not be similar to the single source of truth (aka the data definition might not be consistent throughout an organization) and end up repeating the efforts in creating a unified view of the data.
Strong data governance measures can resolve most of the concerns that come with data democratization. The data governance council and board establish and approve the data policies that are embedded in database systems and owned by data owners and stewards.
Such defined roles and responsibilities ensure data security and abide by regulatory and compliance requirements.
A large section of an organization’s brain power can contribute to this initiative only if it is driven at an org-wide measure. Data literacy and adopting data as a culture should literally run through the veins of the organization and be promoted and incentivized across all the teams.
Training programs help increase the pace of adoption as the data producers and consumers both understand the expectations from data and the impact driven by its insights.
The different teams require data to drive decisions at their work and additionally need multiple tools to ensure that their data is made available in the right format and shape:
The rate of growth of data is overwhelming and so are tools and technologies like a data warehouse like Snowflake, BigQuery, or a business intelligence (BI) tool like Looker, etc.
Data democratization is made quite easy and simplified with the advent of data virtualization tools and software. It is defined as:
“an approach to data management that allows an application to retrieve and manipulate data without requiring technical details about the data, such as how it is formatted at the source, or where it is physically located and can provide a single customer view (or a single view of any other entity) of the overall data.”
Data virtualization comes with many benefits such as the reduced risk of data errors, increased speed of data movement, enabling self-service for end-users, and most importantly increased data governance.
Further, there is also software that does not contain the data itself but points to the meta-data about the actual data and its location. It is a type of meta-database management system which transparently maps multiple autonomous database systems into a single federated database.
Data democratization is a fundamental driver of growth for realizing business value and accelerating growth. Businesses that focus on understanding their dynamic customer needs and improving customer experiences have to level up their game and adopt data democratization as a cultural change.