Team Data Science

MAY 26, 2020

Should you do a masters degree in data science in Germany? Why not, but keep the following in mind! In general, it is very, very practical in Germany because it doesn't cost a lot of money to study. Not like for example in the USA or something like that. So if you are interested in it, you should first think about what the corresponding Master's programme is about.

Data Science 130

Data Science Computer Science Data Engineering Data Engineer 130

Start Data Engineering

MAY 23, 2020

Introduction Approach Project overview Engineering Design Airflow Primer: Setup Code and explanation Stage 1. pg -> file -> s3 Stage 2. file -> s3 -> EMR -> s3 Stage 3. movie_review_stage, user_purchase_stage -> Redshift table -> quality Check data Monitoring ETL Design Review Common Scenarios Next Steps Conclusion Introduction Starting out in data engineering can be a little intimidating, especially because data engineering involves a lot of moving parts.

Data Engineering 130

Data Engineering Data Engineer Project Engineering 130

Data Engineering Podcast

MAY 25, 2020

Summary Gaining a complete view of the customer journey is especially difficult in B2B companies. This is due to the number of different individuals involved and the myriad ways that they interface with the business. Dreamdata integrates data from the multitude of platforms that are used by these organizations so that they can get a comprehensive view of their customer lifecycle.

Machine Learning 100

Machine Learning Portfolio Deep Learning Data Engineering 100

Confluent

MAY 27, 2020

Recently, I’ve been looking at what’s possible with streams of Wi-Fi packet capture (pcap) data. I was prompted after initially setting up my Raspberry Pi to capture pcap data and […].

Kafka 122

Kafka Data Aggregated Data Process 122

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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

Business Intelligence

Team Data Science

MAY 25, 2020

Lot's of people like notebooks and so do I. Jupyter Notebooks for instance, are great to quickly explore some data or try something out. If you want to bring code into production however, you should or most likely, have to write standalone scripts. If you want to create something for production and then do it in production, Jupiter notebooks are not ideal.

Coding 130

Coding Data Engineering Data Engineer Engineering 130

Teradata

MAY 25, 2020

Supply Chain organizations need visibility now to leverage data for making decisions and taking action, both in times of crisis and in relative stability.

Data 111

Data 111

Confluent

MAY 26, 2020

Using a powerful, event-driven application can help you unlock insights contained in the event streams of your business. Before we get into the technology, let’s go over some questions you […].

Building 118

Building Technology Kafka Process 118

Team Data Science

MAY 23, 2020

I love working with Zeppelin notebooks. Its so simple and you can just try something out. Especially working with dataframes and SparkSQL is a blast. What is a Zeppelin? A Zeppelin is a tool, a notebook tool, just like Jupiter. You can run it on a server and you can run it on your Hadoop cluster or whatever. And it can run Spark jobs in the background.

Hadoop 130

Hadoop Data Engineering Data Engineer Coding 130

Teradata

MAY 28, 2020

A team of Teradata data scientists, clinicians & engineers set out to build a model that could track and predict the onset of a Cytokine Storm.

Engineering 76

Engineering Building Data 76

Netflix Tech

MAY 27, 2020

Keeping Customers Streaming?—?The Centralized Site Reliability Practice at Netflix By Hank Jacobs , Senior Site Reliability Engineer on CORE We’re privileged to be in the business of bringing joy to our customers at Netflix. Whether it’s a compelling new series or an innovative product feature, we strive to provide a best-in-class service that people love and can enjoy anytime, anywhere.

Consulting 42

Consulting Engineering Management Systems 42

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

Data

Confluent

MAY 28, 2020

For many organizations, Apache Kafka® is the backbone and source of truth for data systems across the enterprise. Protecting your event streaming platform is critical for data security and often […].

Kafka 113

Kafka Data Security Systems Data 113

Confluent

MAY 29, 2020

This month, we kicked off Project Metamorphosis by introducing several Confluent features that make Apache Kafka® clusters more elastic—the first of eight foundational traits characterizing cloud-native data systems that map […].

Kafka 77

Kafka Project Cloud Systems 77

Teradata

MAY 26, 2020

Many Teradata customers are interested in integrating Teradata Vantage with AWS First Party Services. This Getting Started Guide can help. Read more.

AWS 52

AWS 52