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In the previous post, we briefly mentioned the “Grail – data lakehouse” solution, which is Dynatrace’s response to data challenges such as: their rapid growth, building data logic, automating the process of data collection, analysis and security, or ensuring BIZDEVSECOPS in the “as a code” model. Below, we will introduce the topic in a bit more detail.

Data Management, Data Governance, like any other process and every component of the reality that surrounds us, is subject to changes and challenges, conditioned by both external and internal sources. It is not uncommon, for example, that a trend indicated some time ago, considered a leading or a key one, quickly loses its original attractiveness and becomes a kind of "empty shell", giving way to other solutions, better suited to the current situation. And vice versa – a phenomenon or a tendency previously overlooked, suddenly turns out to be a new, vital element of the whole picture, shaping its current face. So what is the current situation on the Data Governance market (the basis for the analysis will be the material by Robert Rudnicki (GE Bank), presented at the CDO Club meeting in December 2022)?

Reliability engineering (SRE) starts to play recently an increasingly important role. As companies turn to cloud automation and digital transformation to streamline business operations, reliability engineering (SRE) has begun to take center stage. Successful SRE is a team effort. In much the same way that quarterbacks need fullbacks and wingers to win football games, reliability engineers need service level objectives (SLOs) to measure, manage and monitor the results they want. What does it look like in practice? What steps are crucial for SRE to ensure objective success with SLO?

Today, most companies identify data management as a very important part of their data strategy, but most often it happens, just because poor data management is risky. However, it is worth going a step further. To improve the approach to data use and management, these processes need to be democratized and automated. This may require an organizational change, but in the long term there is no alternative to it.

We have already talked and wrote about the fact that data being „the new oil”, however it is an issue that we will touch upon more than once. One of the evidences that data is the most valuable commodity of the 21st century is the data trading exchange, recently established in China.

Recently I was asked for a comment to an interesting discussion about the posts and roles of Chief Digital Officer and Chief Data Officer, which took place during the CDO Club discussing pannel. Here, I would like to elaborate on some comments, that turned up during this meeting – says Ireneusz Suszek, the AZ Frame’s Chief Sales Officer.

A stage that allows for checking the data in a given source. It consists of connecting with the data source, taking a sample of data (the number of records can be pre-defined, e.g. 200 000), and generating reports linked to the source data. Thanks to profiling we get to know a precise data distribution, but we may also find the exceptions to the rules etc. to identify the rules for cleansing the data.

Data verification vs. Data discovery This stage involves physically connecting with the data sources, discovering data models and verifying the data types, which are stored in the columns. Here we can identify: - searching the proper sets of data, - defining the semantics per model.

Only in 2019 global data creation reached the level of 41 zetabytes (zetabyte = 1021). The amount of data produced is currently doubling every three years. The whole world is flooded with data and the global trends are reflected by the amount of data produced by every single company and institution.

Our industry is used to reporting on data in aggregate, which is helpful, yet misses some of the finer-grained detail about your users – whether they’re employees or customers. The problem with this approach is that overall metrics may look positive or neutral, while there are a subset of users who are having a terrible experience. These people may be so troubled by their experience that they decide to leave the company or buy a competitive product. If we can disaggregate that data, we can pinpoint which users are having problems and be more effective at solving them.

As the global pandemic continues, it has become increasingly clear that companies across every industry are planning the "next normal" of their workplace with a much longer-term view.

Every Marathon Runner Has a Story – And So Does Your Data. At least once a year I sit down to watch one of the many televised marathons that happen in cities all around the world.

Precisely, the global leader in data integrity, today released the findings of a report commissioned with market intelligence firm Corinium that examines the significant changes that customer experience (CX) leaders must make as a result of COVID-19, and the acceleration of data-driven technologies shaping the future of CX in the post-pandemic world.

Aternity®, the enterprise-class Digital Experience Management Company™, announced today that it is partnering with Juriba, a leader in Enterprise IT migration software to improve the digital transformation experience for the enterprise.