Navigating the Data Landscape in 2023: 5 Key Trends to Watch

Last week, I got to host a session with Analytics8: Navigating the Data Landscape in 2023: 5 Key Trends to Watch.

A panel of data experts discussed the key trends that companies should pay attention to in order to get more value from their data in 2023. The panel consisted of Patrick Vinton, Kevin Lobo, Christina Salmi, and Tony Dahlager, and the event was moderated by ME, Kate Strachnyi from DATAcated. You can watch the recording here.

The panel identified five key trends that companies should be paying attention to this year, which include:

1. Data Literacy

2. Data Products

3. Data Mesh

4. Event-Driven Architecture

5. Industrialized Machine Learning

Here is a quick overview of what we discussed, along with some quotes from panelists:

1. Data Literacy: “Data literacy is the ability to understand, work with, interpret, and communicate with data in a meaningful way.” Data literacy is crucial for companies that want to get value from their data. With the rise of big data and advanced analytics, it’s important for employees to understand data in order to make informed decisions. It also allows companies to better leverage data in decision making and strategy. Companies are encouraged to assess their employees’ understanding and ability to work with data and identify any gaps in knowledge or skills.
2. Data Products: “Data products refer to the creation of a product or service that uses data as a primary component.” Creating data-driven products and services can set a company apart from its competitors and deliver value to its customers, which can lead to increased revenue and customer satisfaction. Companies can know if they are ready to leverage this by identifying opportunities for data-driven products and services within their industry and assessing their current data infrastructure and capabilities.
3. Data Mesh: “Data mesh is a new architecture that allows for more flexibility and scalability in data management.” Data mesh allows for the creation of a more decentralized and autonomous data infrastructure. This can benefit companies by allowing them to more easily scale and adapt their data management as their business needs change.
4. Event-Driven Architecture: “Event-driven architecture allows for real-time processing of data.” Event-driven architecture enables companies to quickly respond to changes in the market and customer needs, by processing data in real-time. This can give companies a competitive advantage and help them stay ahead of the curve. Companies should assess their current data processing capabilities and identify any opportunities for real-time data processing.
5. Industrialized Machine Learning: “Industrialized machine learning is the use of machine learning in industrial applications.” Industrialized machine learning can improve efficiency and productivity in industries such as manufacturing and logistics. Companies should identify opportunities for machine learning within their industry and assess their current data infrastructure and capabilities.

In conclusion, understanding data literacy, data products, data mesh, event-driven architecture, and industrialized machine learning are key trends to watch in 2023. Companies should focus on these trends to get more value from their data and make informed decisions.