Democratizing data science with the power of AI

by December 8, 2021 0 comments

In this all-digital, work-from-anywhere world, data has never been more important. At the core, every digital transformation is a data transformation. Every company is a data company, every person is a data person, and every process is a data process. The pandemic further highlighted that speed, agility, and empowerment are critical to success — and companies that embrace a data culture adapt, learn, and deliver more value than those that don’t.

Making better decisions with data

With the increasingly diverse sets of data that organizations are collecting, the analytics use cases to transform data into valuable insights are growing just as fast. Today, there are a wide range of tools and focused teams that specialize in finding data insights to inform decision making, but many organizations are struggling to strike the right balance between highly technical data experts and business teams with experience and deep domain expertise.

Not every company has a data science team or Artificial Intelligence (AI) solutions, and those who do, often have a small, highly skilled team with a huge backlog of projects. The business users and analysts with domain knowledge and proximity to business data don’t have the tools or technical skills to do advanced statistical analysis or to manage Machine Learning (ML) projects themselves. They frequently rely on data scientists and ML practitioners to build and deploy custom models through a back-and-forth process of requirements gathering — a process that lacks agility and the ability to iterate quickly.

Financial company TVS Credit is an excellent example of putting data to work in a crisis. In response to COVID-19, it took a structured approach to protect the well-being of employees. A sub-task force set up a dashboard to visualize information related to the health and safety of its team members. Refreshed daily with information collected from employees, regional and area supervisors, the dashboard helps TVS Credit to assess employee needs across several categories, including the health of employees and family members along with any requirements for finance, medicine, food or transport.

Democratizing data science

We’ve seen the power of data and one of the things businesses should be focusing on is how to get more people using data in the daily routine.

Organisations need to apply data analytics in a way that can empower people with the right tools and functionality to help them ask and answer questions, uncover insights, and solve problems. And so, imagine the possibilities if we could democratize data science techniques and empower users to make faster decisions with greater confidence? Enter: Business Science is a new class of AI-powered analytics that allows people with the domain expertise to make smarter decisions faster. Business Science helps domain experts understand the key drivers of a model without having to learn traditional data science tools. Teams can apply advanced analysis to more business problems and make important decisions faster and with more rigor, while still leaning into their human judgment. It’s not about fine-tuning super precise models, but guiding people closest to the problem in the right direction.

After all, business is inherently complicated and unpredictable, so domain experience and knowledge from people who understand the dynamics of their field is critical. And for this reason, Business Science is incredibly valuable for helping to address business problems that a data science team might not be able to allocate resources to or prioritize.

Business science recognizes that not all problems require precision at the expense of speed, and it allows more people with the domain expertise to make smarter decisions faster. In countless scenarios Business Science is the right approach that will result in the best outcome for the business—from lead scoring for marketing and assigning quotas for sales teams, to supply chain distribution and optimization. Human resources might use Business Science to assess the likelihood of a candidate accepting an offer. A real estate team might apply Business Science to plan where to buy office space and explore the costs of moving people from one location to another.

In short, there is less concern about being a programming wizard or an advanced statistician. Business Science provides people with the tools to better answer pressing and specific business questions in a data-driven way. That means all teams can explore their data with predictions, what-if scenarios, forecasting, and many other analytical methods – all with clicks and no code.

The data future looks bright

The need to understand data is only set to grow, and with it, tremendous opportunity to help people and organizations learn and solve problems more effectively. Given the evolving landscape and level of disruption seen in the past year, it is imperative for organizations to democratize advanced analytics, and put data science techniques and AI in the hands of people to ask and answer their own questions, uncover insights, and solve problems.

Prashant Momaya, Director, Solution Engineering, Tableau India

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