Data and analytics trends: Insights for business leaders in 2021
Businesses today leverage on data and analytics to make intelligent business decisions. These help companies see patterns and draw insights that can give them a competitive edge.
Many of the world’s biggest brands are already using data analytics, including Coca-Cola.
In 2017, The Coca-Cola Company director of data strategy and precision marketing Justin De Graaf told ADMA that data has helped them create more relevant content for different audiences.
“We want to focus on creating advertising content that speaks differently to different audiences. Some people love music. Other people watch every sport no matter what time of year. Our brands are already visible in those spaces, and we’re working hard to use data to bring branded content that aligns with people’s passions,” he was quoted saying.
Data analytics is projected to grow in importance in the coming years.
A Deloitte report notes that the field of data analytics is growing in acceptance and importance in today’s complex business environment. It plays a critical role as a decision-making resource for executives, especially those managing large companies.
Data and analytics trends to look out for
Trends in big data and analytics will continue to evolve with the passage of time.
The onus is on business leaders to stay abreast of these trends that can help them cut cost, improve productivity, and enhance their competitiveness, either by implementing the right technology or by hiring the right talent or implementing the right upskilling initiatives for staff.
Here are some of the top data and analytics trends for 2021 by Gartner, a leading research and advisory company, to take heed of:
Smarter, more responsible, scalable AI will enable better learning algorithms, interpretable systems and shorter time to value, said Gartner.
“Organisations will begin to require a lot more from AI systems, and they’ll need to figure out how to scale the technologies — something that up to this point has been challenging,” it said.
They note that AI technology must operate with less data via “small data” techniques and adaptive machine learning. “These AI systems must also protect privacy, comply with federal regulations and minimise bias to support an ethical AI.”
As technology drives growth, CTOs or those in leadership roles will need to ensure they have the right workforce and technology to see these through.
Composable data and analytics
“The goal of composable data and analytics is to use components from multiple data, analytics and AI solutions for a flexible, user-friendly and usable experience that will enable leaders to connect data insights to business actions,” said Gartner.
Gartner’s findings suggest that most large organisations have more than one “enterprise standard” analytics and business intelligence tool.
“Composing new applications from the packaged business capabilities of each promotes productivity and agility. Not only will composable data and analytics encourage collaboration and evolve the analytics capabilities of the organisation, it increases access to analytics,” it said.
Data fabric as the foundation
As data becomes increasingly complex and digital business accelerates, data fabric is the architecture that will support composable data and analytics and its various components, said Gartner.
Talend describes data fabric as “a single environment consisting of a unified architecture, and services or technologies running on that architecture, that helps organisations manage their data. The ultimate goal of data fabric is to maximise the value of your data and accelerate digital transformation.”
Data fabric has plenty of benefits, including enabling accessing, ingesting, integrating, and sharing data in a distributed data environment. It can leverage existing skills and technologies from data hubs, data lakes and data warehouses while also introducing new approaches and tools for the future, said Gartner.