5 Things Every Data Engineer Needs to Know About Data Observability

As a new or aspiring data engineer, there are some essential technologies and frameworks you should know. How to build a data pipeline? Check. How to clean, transform, and model your data? Check. How to prevent broken data workflows before you get that frantic call from your CEO about her missing data? Maybe not.

By leveraging best practices from our friends in software engineering and developer operations (DevOps), we can think more strategically about tackling the “good pipelines, bad data” problem. For many, this approach incorporates observability, too.

Jesse Anderson, managing director of Big Data Institute and author of Data Engineering Teams: Creating Successful Big Data Teams and Products, and Barr Moses, co-founder and CEO of Monte Carlo, share everything you need to know to get started with this next layer of the data stack.

#data-engineering #data #devops #data-science #data-observability

What is GEEK

Buddha Community

5 Things Every Data Engineer Needs to Know About Data Observability

5 Things Every Data Engineer Needs to Know About Data Observability

As a new or aspiring data engineer, there are some essential technologies and frameworks you should know. How to build a data pipeline? Check. How to clean, transform, and model your data? Check. How to prevent broken data workflows before you get that frantic call from your CEO about her missing data? Maybe not.

By leveraging best practices from our friends in software engineering and developer operations (DevOps), we can think more strategically about tackling the “good pipelines, bad data” problem. For many, this approach incorporates observability, too.

Jesse Anderson, managing director of Big Data Institute and author of Data Engineering Teams: Creating Successful Big Data Teams and Products, and Barr Moses, co-founder and CEO of Monte Carlo, share everything you need to know to get started with this next layer of the data stack.

#data-engineering #data #devops #data-science #data-observability

 iOS App Dev

iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Gerhard  Brink

Gerhard Brink

1621413060

Top 5 Exciting Data Engineering Projects & Ideas For Beginners [2021]

Data engineering is among the core branches of big data. If you’re studying to become a data engineer and want some projects to showcase your skills (or gain knowledge), you’ve come to the right place. In this article, we’ll discuss data engineering project ideas you can work on and several data engineering projects, and you should be aware of it.

You should note that you should be familiar with some topics and technologies before you work on these projects. Companies are always on the lookout for skilled data engineers who can develop innovative data engineering projects. So, if you are a beginner, the best thing you can do is work on some real-time data engineering projects.

We, here at upGrad, believe in a practical approach as theoretical knowledge alone won’t be of help in a real-time work environment. In this article, we will be exploring some interesting data engineering projects which beginners can work on to put their data engineering knowledge to test. In this article, you will find top data engineering projects for beginners to get hands-on experience.

Amid the cut-throat competition, aspiring Developers must have hands-on experience with real-world data engineering projects. In fact, this is one of the primary recruitment criteria for most employers today. As you start working on data engineering projects, you will not only be able to test your strengths and weaknesses, but you will also gain exposure that can be immensely helpful to boost your career.

That’s because you’ll need to complete the projects correctly. Here are the most important ones:

  • Python and its use in big data
  • Extract Transform Load (ETL) solutions
  • Hadoop and related big data technologies
  • Concept of data pipelines
  • Apache Airflow

#big data #big data projects #data engineer #data engineer project #data engineering projects #data projects

Uriah  Dietrich

Uriah Dietrich

1618137000

Data Observability: How to Fix Data Quality at Scale

Companies spend upwards of $15 million annually tackling data downtime, in other words, periods of time where data is missing, broken, or otherwise erroneous, and 1 in 5 companies have lost a customer due to incomplete or inaccurate data.
Fortunately, there’s hope in the next frontier of data: observability. Here’s how data engineers and BI analysts at Yotpo, a global eCommerce company, increases cost savings, collaboration, and productivity with data observability at scale.
Yotpo works with eCommerce companies across the world to help them accelerate online revenue growth through reviews, visual marketing, loyalty and referral programs, and SMS marketing.
For Yoav Kamin, Director of Business Performance, and Doron Porat, Data Engineering Team Leader, having consistently accurate and reliable data is foundational to the success of this mission.

#data-analysis #data-observability #data-engineering #data-quality #data

 iOS App Dev

iOS App Dev

1624072920

10 Must-have Skills for Data Engineering Jobs

Big data skills are crucial to land up data engineering job roles. From designing, creating, building, and maintaining data pipelines to collating raw data from various sources and ensuring performance optimization, data engineering professionals carry a plethora of tasks. They are expected to know about big data frameworks, databases, building data infrastructure, containers, and more. It is also important that they have hands-on exposure to tools such as Scala, Hadoop, HPCC, Storm, Cloudera, Rapidminer, SPSS, SAS, Excel, R, Python, Docker, Kubernetes, MapReduce, Pig, and to name a few.

Here, we list some of the important skills that one should possess to build a successful career in big data.

1. Database Tools
2. Data Transformation Tools
3. Data Ingestion Tools
4. Data Mining Tools

#big data #latest news #data engineering jobs #skills for data engineering jobs #10 must-have skills for data engineering jobs #data engineering