How Machine Learning Is Powering Data Management

May 4, 2020

For a long time, artificial intelligence and machine learning seemed like elusive technologies that may never emerge with measurable benefits for enterprises. Now, machine learning is equipping data management to produce new levels of productivity, better analysis, and improved efficiency. Here are a few of the areas machine learning is better equipping data management:

Taking Over Table Structures: Business decisions, no matter how great the data, require human analysis, so it’s helpful when machine learning can take over mundane things like determining table structures. With the help of machine learning, line of business managers are able to look at the dynamic structure within data while eliminating static restrictions at the outset. This allows for the harvesting of data from sources that were considered unsuitable in the past.

Identify Bad Data and Suggest Corrections: Artificial intelligence and machine learning are contributing in other ways to data management, such as predicting table growth for capacity planning purposes. They are also engaging in self-management and identifying anomalies. Promoting data quality gets a boost from machine learning because it can look for bad data and even suggest corrections for improving the data content.

Configuration: Configuration and workload management are also areas impacted by machine learning because individual settings can be determined using machine learning algorithms. Similarly, machine learning supports security efforts by identifying abnormal data access, including sessions where users are accessing large amounts of data and using unusual selection criteria.

Query management is another potential use for machine learning because it can be utilized to find the source of long-running queries. It can also flag users when they are about to place a disproportionately large data set on the database so that they can be scaled at different times of day to preserve user experience.

Forecasting and Failure Prevention: Machine learning catalogs the data being processed and uses it to predict outcomes and prevent unfavorable outcomes. It can also be used to quickly respond to customer preferences and behaviors in order to improve the customer experience.

The Impact on Data Management Jobs

There’s a lot of discussion about how machine learning impacts data management jobs, with experts divided. Some say that the jobs in this area will be “upskilled,” with more diverse backgrounds in data architects and fewer workers in the role of database administrator.

Some expect that DBAs will shift from data cleanup and troubleshooting to quality, stewardship, and creating additional value rather than simply managing the data. A more strategic role will allow DBAs to be involved with providing guidance on how to use data management to better forecast and predict future results.

The Risks

Along with the question of how machine learning will impact jobs, data management professionals also caution that there is some risk associated with relatively new technology, resulting in the need for careful planning. Enterprises should avoid rushing into machine learning without proper architectures and a plan for how it may impact user experiences for those that access the data.

Artificial intelligence and machine learning also require high levels of computing power, which increase costs. Additionally, the right talent needs to be in place so that there are human checks on processes being considered for machine learning.For more information about how machine learning is shaping database management, contact us at Access Tech. We can provide guidance to create a plan for implementing machine learning safely in your organization.

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