Decision Intelligence – The key trends in data science and analytics for CIOs and CEOs

by Yara El-Sabagh

Decision Intelligence – OUT NOW im #ConfareBlog: The key trends in data science and analytics for CIOs and CEOs

We find ourselves in a data revolution; the path to data-driven business has never been so accessible. Low-code applications and the increased awareness of users and management of the possibilities that data science and analytics give them are leading the way. In the run-up to the Confare Swiss #CIOSUMMIT, we wanted to know more not just the methods and opportunities, but also the stumbling blocks of data transformation.  Sean Jackson from Pyramid Analytics shares his thoughts below.

Meet the experts from Pyramid Analytics and more than 200 top-class IT professionals in person at the most important IT management meeting event in Switzerland – the Confare Swiss #CIOSUMMIT.

What is the status of data science in organizations today?  Where is it working?  Where is there still potential?

We are living through a data revolution, plain and simple. More data is being created every day—by businesses, individuals, data providers—than ever before. Future-focused organizations know the key to their ongoing success will be their ability to capture the right data, analyze it, and incorporate the resulting insights into their decision-making processes.

For these reasons, data science has become a hot topic, even as data science experts are in short supply. At the same time, advances in machine learning are making data science practices more accessible to experienced analysts without a full data science background and training.

This growing field of expertise has already shown its value. However, implementing data science at scale across large, complex organizations is often still a herculean task, especially for those without an existing data science practice.

Many organizations are focused on unlocking the potential of their own data.  Where are there still obstacles as companies aim toward becoming a data-driven business?

Becoming data-driven is more possible than ever. In general, more data is available to be analyzed; more people want to use that data to make decisions; and increasingly sophisticated analytics are in high demand.

However, there are challenges at every turn:

  1. Accessing the right data can be difficult, especially at high volumes, causing delays or complete roadblocks.
  2. Traditional self-service tools are idiosyncratic and overly technical for most people.
  3. Multiple deployments of these BI tools create silos of information, inconsistent data, and multiple versions of “the truth.”

Thankfully, there is a better way, and it’s called “decision intelligence.”

In practical terms, what does Decision Intelligence mean and how are organizations benefiting?

Decision intelligence is what’s next in analytics. It addresses the shortfalls of current fragmented approaches that frustrate the leaders responsible for data and analytics strategies. It is designed to help innovative leaders catapult their organization’s data and analytics capabilities to the next level along three key dimensions: data, people, and analytical capabilities, from the simple to the sophisticated.

Organizations that have embraced decision intelligence are finding efficiencies and value at every turn. Specifically, these benefits result from the ability to speed up actionable insights, scale adoption of decision intelligence methods, and simplify the analytics and decision process, from seemingly simple queries to the very complex.

What role do low-code platforms play in Decision Intelligence?

One of the great promises of decision intelligence is that it is for any person. That is, decision intelligence brings the benefits of data-driven decision-making to more people than ever before. In order to scale analytics adoption, people need access to a decision intelligence platform that is both powerful and flexible enough for the needs of technical uses and data scientists, as well as intuitive and user-friendly enough for non-technical and business use-cases.

A low-code (or no-code) platform is ideal for an enterprise-wide deployment because it has the potential to support the full spectrum of user needs within one consolidated system.

How is data science being perceived by business leaders?  What trends and developments should C-level execs keep an eye on?

The World Economic Forum, in its Future of Jobs Report 2020, predicts that the job with the highest growth and demand by 2025 will be ‘data scientist.’ Already, hiring people with the skills and training of a data scientist is difficult, even for those with the desire and resources to do so.

For that reason, it is likely that the role of “citizen data scientist” is an equally important and growing role. With access to the right tools—specifically, those empowered by thoughtful and nuanced applications of machine learning and AI—people with experience as a data analyst can produce the valuable insights and predictive analytics typically limited to the practice of data science. Investing in platforms that integrate augmented analytics technologies can have the same level of impact as hiring the right innovative people.

What role does Pyramid Analytics play in a CIO’s ecosystem?

The Pyramid Decision Intelligence Platform is built to help automate the decision-making process to empower anyone to make faster, more intelligent decisions with any data, for any person and any analytics need. The platform combines three core processes—data prep, business analytics, and data science—to unify the entire decision workflow.

Für Sie ausgewählt

Leave a Comment