Data Science strategy of Oracle


California-based American multi-national company Oracle deals with database software and technology, cloud engineering systems, and enterprise software products. Oracle DBMS is the most generally used database management system for cost-efficient solutions for applications and data management. It uses SQL as a query language to interact with the database. Oracle is also among the dominant 100 largest firms in the world regarding its market value.

The company wants individuals to see data through new perceptions and alternative ways that nobody has ever thought of before and wants their folks to know about the unnoticed and foreign capabilities of data. In order to this, Oracle designs manufacture, and sells both software and hardware products.

 Recently, the company declared the availability of its OCDS platform. This is a cloud data science platform for entrepreneurs for teaching, training, administering, and setting up machine learning models.

With the dimensions and variety of social, mobile, and device data, along with new technologies and tools, data science now plays a deeper role than ever before. The business considers data science and AI to be a technology-enabled strategy. Data is shifting the way we look at things, the way we carry out our daily tasks, and whatnot. Since our daily life revolves around data or data science, it is indeed one of the most relevant skills to learn and master in the 21st century. The company is on a mission to improve the data science teams in all terms with better capabilities, such as shared products, model catalogs, team security policies, reproducibility, and audibility. The Oracle Cloud Infrastructure Data Science selects the most optical training datasets automatically. It does it through AutoML, Automated predictive feature selection, model evaluation, and explanation.

Main features and advantages of Oracle Cloud Infrastructure Data Science

• Automated data science workflow

• Saves time

• Limited errors with capabilities like AutoML

• Automated predictive feature selection

• Model evaluation

• Model explanation

Back in 2018, Oracle had acquired, and this is where the origin of Oracle’s Cloud Data Science lies. They mainly built this for data science teams and scientists. This also makes us think about the efforts of Oracle to integrate both artificial intelligence and ML into its cloud infrastructure.

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