K
Kathleen Martin
Guest
The speed of growth often outpaces the rate at which enterprises figure out concrete ways to manage, integrate and leverage data actionably. Some trends become staples (like Salesforce.com), and others go down in history as just a fad (like Netezza and other data warehouse “appliances”).
Now, as we have settled into 2022 and have a clearer picture of what enterprises are prioritizing this year in data management, five emerging trends show potential to last. Data teams will need to catch the wave early and effectively to stay competitive.
Top Five Data Management Trends for 2022
Predicting and preparing for trends is necessary in a world that evolves as fast as ours. Here are the key trends that we’ll see playing out over the course of this year.
Trend #1: Demand for real-time capabilities fueling the return of change data capture
As data teams deal with the distribution, diversity and dynamic nature of the expanding data universe, they need to be able to understand what changed, when it changed, and the order in which it changed on each update. We see more teams turn to log-based, queryable historic changelogs to follow every update.
The focus is not just on the speed of replication but also on the precision to feed use cases like AI model training, fraud detection and real-time marketing campaigns. With change data capture, data teams have visibility into all the changes laid out in chronological order. This expands possibilities to more compelling use cases than just copying a snapshot of the data from point A to B. Change data capture is best deployed on large source databases, which may have a high, or sporadic, update schedule to a smaller fraction of the overall table size. The latency of incremental changes and the time it takes to update them are minuscule.
Trend #2: Operational analytics moving into the cloud data warehouse
The scale and elasticity of the cloud data warehouse have made it the backend system of the business. Enterprises are finding new, creative avenues to take advantage of the rich data in these platforms and fit different data pieces together. Data sharing is making this increasingly more common.
Continue reading: https://www.toolbox.com/tech/data-management/guest-article/data-management-trends-to-keep-an-eye-on/
Now, as we have settled into 2022 and have a clearer picture of what enterprises are prioritizing this year in data management, five emerging trends show potential to last. Data teams will need to catch the wave early and effectively to stay competitive.
Top Five Data Management Trends for 2022
Predicting and preparing for trends is necessary in a world that evolves as fast as ours. Here are the key trends that we’ll see playing out over the course of this year.
Trend #1: Demand for real-time capabilities fueling the return of change data capture
As data teams deal with the distribution, diversity and dynamic nature of the expanding data universe, they need to be able to understand what changed, when it changed, and the order in which it changed on each update. We see more teams turn to log-based, queryable historic changelogs to follow every update.
The focus is not just on the speed of replication but also on the precision to feed use cases like AI model training, fraud detection and real-time marketing campaigns. With change data capture, data teams have visibility into all the changes laid out in chronological order. This expands possibilities to more compelling use cases than just copying a snapshot of the data from point A to B. Change data capture is best deployed on large source databases, which may have a high, or sporadic, update schedule to a smaller fraction of the overall table size. The latency of incremental changes and the time it takes to update them are minuscule.
Trend #2: Operational analytics moving into the cloud data warehouse
The scale and elasticity of the cloud data warehouse have made it the backend system of the business. Enterprises are finding new, creative avenues to take advantage of the rich data in these platforms and fit different data pieces together. Data sharing is making this increasingly more common.
Continue reading: https://www.toolbox.com/tech/data-management/guest-article/data-management-trends-to-keep-an-eye-on/
