In today’s age of innovation and transformation, data is the weapon and analytics is the strategy for victory. But with access to vast amounts of data, comes the big responsibility of storing it correctly.
Database management workloads are at a tipping point with the quantity of data and segregation categories increasing exponentially.
Many IT officers and executives are manually updating databases, analyzing the data and creating reports, which wastes time that could have otherwise been put to more productive use.
Data warehouse automation is key to developing a competitive edge. Regardless of the type of company you run, there are 3 essential ingredients of data warehouse automation:
Creating and operating a data warehouse must be a simple “LOAD AND GO” process.
Employees should be able to identify tables, load data, and run their workloads in short order. All management tasks should be fully automated, including database-tuning chores. Data must be automatically compressed and encrypted.
Data warehouse automation must be elastic, in terms of computing and storage capacity.
This will allow you to scale up or down, with little downtime. It should also support business intelligence tools and services as well as data integration tools and services. This enables firms to use existing tools and incorporate new tools to enhance analytics and insights.
Automated data warehouses offer fast data solutions, such as data segregation.
Adaptive machine learning automatically tunes the database, helping to deliver unmatched performance. This boosts employee productivity and enables better and faster decision-making processes.
Data warehouses are moving to the cloud because current systems are difficult to manage effectively with growth among data and users or are too slow to deploy. If you are facing these same issues and want a cloud solution that is flexible and scalable, click the link below for more information.