Open Telekom Cloud for Business Customers

The art of taming the data beast

by Redaktion
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The Open Telekom Cloud supports your journey to a data-driven enterprise. 

In this article you will read about

  • how you can support your path to a data-driven enterprise with the Open Telekom Cloud,
  • which Open Telekom Cloud service you can use to introduce efficient data governance, and
  • what other functionalities DataArts Studio contains.

Formerly actions, today data: Data-based decisions in the "data-centric enterprise" are the big vision for business in the future. Decisions are no longer based on gut instinct, but are made on the basis of data analyses. And artificial intelligences, the great productivity assistants of the future, devour insane amounts of data in their hunger for training. These are just two examples of the outstanding importance of data.

Data as the top topic of digital transformation

There is more than enough data. Never before has mankind collected more data than today. Even kids are using wearables to record their daily step workload; networked sensors, cars, machines, cell phones, cameras, satellites, and even business applications are expanding the data universe by unimaginable amounts every second. Data is a top issue in the digital transformation. Only companies that manage to handle data masterfully and avoid all data pitfalls will succeed in leveraging the added value of a data-centric future.

If you're lucky, you'll only be confronted with the results of the analyses – in the form of fancy dashboards that allow flexible evaluations. But the road ahead is rocky and arduous. Data analytics is hard work. It starts with confusing Excel spreadsheets, on which risk controlling officers desperately search for errors in the database during night shifts.

The age of data silos

Typically, however, the problems with data begin well before an Excel spreadsheet, dashboard, or data warehouse. The world of data is confusing. Countless data formats in a wide variety of systems make for a veritable data jungle. Many experts report that at the beginning of Big Data analytics or artificial intelligence training is the grueling task of first sifting, sorting and unifying the (hopefully available) data. Typically, 80 percent of the actual project time goes into such preliminary work. The actual analysis or training, on the other hand, is comparatively uninvolving. The bottom line: a bit like Domino Day – two months to set up for one hour of fun. Except that in a data-centric company, that happens every day.

In search of efficient data management

Efficient data management – especially against the background of existing historical data inventories – should be high on the agendas of enterprise digitization. The central question here is: To what extent can tools relieve people of these manual tasks?

With DataArts Studio (DARTS), the Open Telekom Cloud now also offers a comprehensive solution for data governance. Data governance stands for the efficient management of data in an organization. Rules, processes and policies are used to ensure that data is reliable, secure and accurate. And that those who need it have access to it – and only them. So data governance also takes care of the rights to the data.

The dream of data governance is high-quality, correctly stored and protected data, so that errors and misunderstandings in data use are minimized.

The role of DataArts Studio

DataArts Studio, a new service on the Open Telekom Cloud, breaks down data silos. It is an elegant tool for integrating and harmonizing data from different sources (departments, systems, databases) in different formats and structures. DataArts Studio thus supports the ETL process (Extract, Transform, Load) – even for data sources external to the company.

Grafik DataArts Studio

DataArts Studio is based on a data lake and provides various data management functions. It can also work with MRS Hive or GaussDB (DWS) and traditional enterprise databases such as Oracle and MySQL, among others. It thus also builds a bridge between the different IT worlds. For data development, i.e. the preparation and processing of data, own processes can also be defined in different programming languages.

The data management platform relieves data analysts of a multitude of tedious tasks and accelerates the provision of data for analyses or AI training.

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