Atlan, a data democratisation startup, recently secured $2.5 million in series A funding. It works with more than 200 companies across the globe, helping enterprises collaborate easily on data projects. Atlan’s products facilitate the democratisation of data, both internal and external, thereby enabling enterprises to collaborate on data projects.
Another startup, Graphext, is on a journey to transform data science for business, by developing a universal data science software tool that can be used by everyone all across the globe in an efficient manner.
The need for these startups has only become prominent with time and are openly welcomed as it allows for the data science community to communicate with each other and data problems with much more ease. Enabling data democratisation, they are bringing about an improvement in product development while addressing other challenges in data scientists’ workflow.
What Do Data Democratisation Startups Offer?
In this digital age, to win with data, the data science community need to collaborate effectively to bring the most effective use case for data. These startups, Atlan for instance, are building the glue or the collaboration layer for these diverse teams to make them more agile and efficient. As the Atlan founder, Prukalpa Sankar says, just the way HubSpot created a home for marketing teams and GitHub created a home for engineering teams, we are creating a home for data teams.”
There is a huge challenge that comes into picture when diverse individuals in the companies struggle to collaborate efficiently on a data science project, often resulting in project failure. It is an era of consumerisation of enterprises and a sharp focus on data democratisation will help to reimagine the future of how data teams work, which many startups are now working to offer companies at much ease.
For instance, there are startups offering democratisation of data analysis and data analytics tools can allow end users to effectively analyse and create report and insights. It allows for incorporating vast amounts of data and perform near-human feats of discrimination, correlation and predictive analysis at scale.
Why Do We Need Data Democratisation?
Companies today are dealing with a large number of complex datasets. Analysing these datasets is an answer to complex questions, but while everyone wants to be data-driven, only a few data scientists are able to perform the task of analyzing complex data. Many a time the tools are unfriendly or inaccessible to the general public, making it difficult for them to access it. Or at other times it is difficult to collaborate on a single platform.
While most companies such as Uber, Netflix and others are now providing instant access to business data, as a part of their technology-centric approach, there are many others that have to still adopt this strategy. This has allowed for an easy understanding of the data points while coming up with solutions for challenges that they might face.
By making data available throughout their organisation, these companies allow accessibility on the expected use of data in the near real-time.
What Issues Can Data Democratisation Overcome?
With data democratisation, companies can make easy plans for the future, observe what is going on inside and outside their business, react instantly when something changes, and reallocate resources as necessary.
Issues that data democratisation help overcome are:
- Acquisition of external data by data scientists take months currently which could be done in minutes
- Sharing data is not as easy as it looks. It may have issues such as size and format if shared on different platforms, which can be easily overcome
- Non-accessibility of a convenient data profile
- Making a product workflow incredibly easy for non-specialist users to access and use data of any scale and size without needing to download it
The need for the startups that can enable data democratisation, therefore, comes into the picture. Companies can leverage solutions from these startups to go about with easy accessibility of data and increased collaboration. It can not only bring about an ease of conducting business in organisations but for the teams to collaborate efficiently on the same business front.
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Srishti currently works as Associate Editor at Analytics India Magazine. When not covering the analytics news, editing and writing articles, she could be found reading or capturing thoughts into pictures.