Home 2019-03-11T16:13:18+00:00

Hybride DWH-Architekturen: Mehrwerte von Cloud Services (Teil 2)

Von | 16. Januar 2019|

Wie lassen sich hybride Technologien im Data-Warehouse kombinieren? Wie tragen erhöhte Agilität und schnelle Innovationszyklen der Hersteller zur Optimierung von Betriebskosten im Cloud-Kontext bei? Teil 2 unserer dreiteiligen Artikelserie über hybride DWH-Architekturen.

Kürzlich wurde das Buch BI & Analytics in der Cloud im dpunkt-Verlag veröffentlicht, in dem von verschiedenen Fachautoren des TDWI die Besonderheiten zu Cloud Bus

Hybride DWH-Architekturen: Mehrwerte von Cloud Services (Teil 1)

Von | 14. Januar 2019|

Wie passen Cloud und Data-Warehousing zusammen, wie wird Connectivity in die Cloud hergestellt und welche Skalierungsmöglichkeiten und Chancen ergeben sich dadurch? Teil 1 unserer dreiteiligen Artikelserie über hybride DWH-Architekturen.

Kürzlich wurde das Buch BI & Analytics in der Cloud im dpunkt-Verlag veröffentlicht, in dem von verschiedenen Fachautoren des TDWI die Besonderheiten zu Cloud Bus

Why You Should Test Your Kubernetes Network Policies

Von | 10. Januar 2019|

Kubernetes Network Policies appear to be a relatively simple solution for controlling traffic in and to a cluster. But after looking more closely we found that they sometimes behave differently than expected. Here's what we've learned.

Kubernetes Network Policies appear to be a relatively simple solution for controlling traffic in and to a cluster. But after looking more closely we found that they s

Grafana Loki: Scalable and Flexible Logfile Management

Von | 08. Januar 2019|

Loki is a logfile aggregator that collects log streams. It does so by storing log streams as well as labels attached to them. Loki works like Prometheus, but for logs. Each log stream is indexed and its occurrence is tracked via a timestamp.

Right now there are three popular platforms to build a scalable and flexibel logfile management solution on-premise: splunk, elastic stack and graylog. Most customers

Deep Learning Fundamentals

Von | 07. Januar 2019|

This article unveils the connections between artificial intelligence, machine learning and deep learning based on a simple example. It suits as an introduction for newbies as well as a reference point for advanced readers looking for more complex content.

There has always been a gap between the capabilities of men and machine. While computers were able to perform complex multiplications or store large amounts of data,

MLaaS: Maschinelles Lernen in der Cloud

Von | 13. Dezember 2018|

Machine learning as a service (MLaaS) bietet Unternehmen eine einfache Möglichkeit, Daten zu verarbeiten, Modelle zu trainieren und Prognosen zu erstellen. In diesem Artikel werden die Angebote von vier der größten Cloud-Anbieter vorgestellt: GCP, AWS, MS Azure und IBM Cloud/Watson.

Cloud Computing gewinnt durch sein flexibles Bereitstellungsmodell immer größere Bedeutung. Von Software (SaaS),Plattformen (PaaS) bis hin zur IT-Infrastruktur (IaaS)

Remote Work: 12 Guidelines for a Successful Remote Team

Von | 05. Dezember 2018|

Two years ago when someone mentioned remote work to me, the first picture which came into my mind was the surfing colleague on an exotic island not available because of the lack of broadband connection. My perception was, remote work can not be productive nor can it be efficient or fun. Oh how wrong I was ...

Two years ago when someone mentioned remote work to me, the first picture which came into my mind was the surfing colleague on an exotic island not available because

4 Ways to Manage Your OpenStack Secrets with Terraform and git

Von | 29. November 2018|

Terraform and OpenStack provide some clever ways of authenticating to OpenStack and configuring your clouds. This article shows you four easy ways so you never have to worry about accidentally uploading secrets to places where they shouldn't be.

Uploading secrets (i.e. passwords and usernames) to version control is an obviously terrible idea. Yet, there are almost 450,000 commits to github for the search term

Traditionelles vs. virtuelles Data Warehouse: Vergleich der ETL-Performance

Von | 26. November 2018|

Durch die Virtualisierung von ETL-Prozessen kann eine DWH-Architektur an Flexibilität gewinnen, allerdings resultiert daraus eine reduzierte Performanz. Hier sind die Ergebnisse meiner Masterarbeit, in der ich diesen Trade-off eines virtuellen Data Warehouse untersucht habe.

Durch die Virtualisierung von ETL-Prozessen kann eine Data-Warehouse-Architektur an Flexibilität gewinnen, der daraus resultierende Nachteil ist eine reduzierte Perfo

Working efficiently with Jupyter Notebooks

Von | 20. November 2018|

Being in the data science domain for quite some years, I have seen good Jupyter notebooks but also a lot of ugly ones. Follow these best practices to to work more efficiently with your notebooks and strike the perfect balance between text, code and visualisations.

If you have ever done something analytical or anything closely related to data science in Python, there is just no way you have not heard of or IPython or Jupyter not

AWS ECS: Kickstart Containers into Production

Von | 12. November 2018|

There are quite some ways to bring containers into production, e.g. Kubernetes, Openshift or Docker Swarm. This article will present another viable addition to this list: Elastic Container Service on AWS (AWS ECS) as solution to run containers at scale.

There are quite some ways to bring containers into production, e.g. Kubernetes, Openshift or Docker Swarm. This article will present another viable addition to this l

Rethinking Modern Data Warehouse with Azure Analysis Services

Von | 07. November 2018|

Azure Analysis Services is able to consume data from a variety of sources including storages like Azure Blob Storage or Azure Data Lake Store. Here's how you lift our file-based data directly to Azure Analysis Services.

Before I got more familiar with Microsoft Azure and all its PaaS components such as Azure Analysis Services, I was routinely sticking to Microsoft’s on-premises BI st

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