What we're about

The life cycle of data, from creation to obliteration, touches a wide range of technologies, systems, processes, solutions - and people. Typically, we professionals only see the part of the overall picture that are tangent to our role and are truly proficient in a comparatively narrow range. This group offers the opportunity to widen your understanding, to get insights into all the many aspects of the data platform. This will give you a better understanding of challenges and solutions and make your more effective - and valuable - in your profession.

We cover the overall data platform that supports the “Data Driven Enterprise”. If you’re a DBA, or a tamer of Big Data, a Data Engineer, an Integrator, a Data Scientist or an Analyst - simply said, a professional running data through your hands, or turning data into information - this Meetup group is tailored for you. Members of this group know that data is much more than simply “the new oil” - it becomes more useful the more it is used and over time often reveals further applications, supporting innovation and driving business.

Although this group initially is sponsored and hosted by Oracle, the meetings are declared to be truly vendor neutral. Any informative topic from any private or employed person is most welcome.

Meetings include presentations that serve as introductions and overview to a specific topic, which we then discuss openly.

For Zurich, initially and until co-leads come on board (as said, we are vendor neutral) the meetings are hosted at a perfect location, the Oracle "Smart Innovation Center" in the Prime Tower (Hardbrücke).

Upcoming events (1)

Data Lineage w. Graph DBs & DB Programm. - from active DBs to NoSQL/Cloud Comp.

Session 1: Data Lineage made easy with Graph Databases Speaker: Gianni Ceresa, DATAlysis GmbH, Analytics & EPM Consultant Abstract: Data Lineage has always been a topic, at least for auditing, and came back as a key element with regulations like GDPR and similar. The problem is that with the multiplications of tools, sources, transformations and movements of data it's getting harder and harder to have a clear picture of the whole data lineage in a company and even more complicated to use that information for auditing. This is where graph databases jump in to make things easier: data lineage is by nature a graph. It's possible to model every single flow, every single component down to a column in a database or a dashboard. Add the whole corporate security on top with the various abstraction layers of groups and roles on top of users and your graph is ready for analysis. This talk will cover why graph databases are a perfect match for data lineage and use an analytical enterprise platform as example, tracking a single column from a database table to the very end into dashboards and reports and the respective security. (Based on Oracle Property Graph engine PGX with Cytoscape for visualization, and OAC/OBIEE for the data lineage example). Session 2: Database Programming - From Active Databases to NoSQL and Cloud Computing Speaker: Bastian Hossbach, Principal Member of Technical Staff for Oracle Abstract: Database applications define highly complex business logic that cannot be expressed purely in SQL. This prevented them from being moved completely into the database in order to achieve high performance. Therefore, vendors of relational databases started eventually to provide procedural extensions to SQL such as PL/SQL (Oracle Database), SQLPL (IBM DB2), T-SQL (Microsoft SQL Server), or PL/pgSQL (PostgreSQL). Due to the introduction of server-side programming languages, databases began to shift from being absolutely passive to becoming more active. Along with the rapid growth of some Web companies, radically new approaches to data management, known as NoSQL, emerged. NoSQL databases broke with not only how data is stored and maintained, but also how it is accessed and processed. Everyday programming languages such as Java (e.g., Apache Hadoop), Erlang (e.g., Riak), or JavaScript (e.g.,MongoDB, CouchDB) were simply used as the query language. While the need for stronger consistency or SQL stroke back in many cases, the demand for supporting modern programming languages in databases remained. With the ongoing transition to cloud computing, developers now want to keep their preferred programming languages and environments when switching to database-side bprogramming. Consequently, vendors of cloud databases try to support multiple popular programming languages such as JavaScript, R, and Python (e.g., Microsoft Azure Cosmos DB [NoSQL], Amazon Redshift [SQL]). In this lecture, we will review the common history of databases and programming languages, give an introduction into database-side programming for some relevant systems, and discuss the challenges of effectively and efficiently integrating modern programming languages with databases.

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