Democratizing Access to data

Democratizing Access to data

There’s a growing need to put data to work at all levels of a company. The ability to democratize data is a strong predictor of any company success or failure.

Nowadays every business get consistently inundated with data from every angle and every possible source, from web analytics to transactional data up until IOT sensors and beacons. As organizations look to become more agile and competitive, all pathways generate huge amounts of data at all times. However, the challenges and opportunities of putting data to figure are growing exponentially.

As a results of this incredible amount of knowledge to process and the new tech that helps non-technical people constantly look into and generate new and different datasets, there’s desire and demand for data democratization, easier access to data at all levels of the organization.

Data democratization means everybody has access to data and there are not any gatekeepers that make a bottleneck at the gateway to all the information. The goal is to possess anybody use data at any time to form decisions with no barriers to access or understanding. It requires that we accompany the access with a simple way for people to know the info in order that they will use it to expedite decision-making and uncover opportunities for an organization.

In fact, democratizing data is at the heart of digital business, empowering more people within an organization to extract the insights that inform decisions. Data democratization allows those experts to share their knowledge, and makes it possible for workers across the corporate to get their own data insights.

In order to achieve a successful data transformation and democratization, two main goals need to be achieved:

  1. Understanding the business and domain so in order to define the use cases with the highest impact. Any data project needs to have clear business objectives with well-defined business hypotheses.
  2. Create a roadmap for creating a source of truth and consolidating different data sources, along with the required pipelining. This step requires deep domain knowledge to successfully understand the landscape from business data as well as data engineering skills to deal with large and complex data.

Companies recognize that data may be a strategic asset and strive to adopt a data-driven culture. Through data-based decisions, businesses can more effectively seek to realize their desired business outcomes. However, this can only be achieved if a data democratization process is already in place at all levels of the organization.

At the foremost basic level, data democratization means breaking down silos and providing access to data when and where it’s needed at any given moment. It’s all about building an IT platform that supports more agile and versatile alignment and decision across the org.

A separate data science organization, insulated from the company, cannot efficiently produce insights and guide decision making. All data initiatives must reach across an organization and beyond, touching employees at all levels of the enterprise, as well as business partners and contractors

Until recently, data was “owned” by IT departments. Business units like marketing, business analysts and executives used the info to form business decisions, but they always had to travel through the IT department before being utilized. And unfortunately, to this day, due to legacy thinking and lack of relevant innovation in the space, some companies find themselves still aligned with this line of thinking.

In many cases, IT infrastructure gets mired in red tape and the existing infrastructure would not cut it and more is required and then who pays for it comes up.

Cloud infrastructure can be looked at to resolve some of this, along with source consolidation, top down culture shift towards data driven decision-making.