Databand.ai

JULY 17, 2023

DataOps vs. MLOps: Similarities, Differences, and How to Choose Joseph Arnold July 17, 2023 What Is DataOps? DataOps , short for Data Operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data management processes.

Data Pipeline 52

Data Pipeline Machine Learning High Quality Data BI 52

Monte Carlo

AUGUST 9, 2023

And in the last 5-ish years, DataOps has entered the scene to help data engineers scale data management. This modern approach has been a game-changer for data engineering teams, whose processes have always been prone to breakages. But what, exactly, is a data engineering workflow? Let’s dive in.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Pipeline 52

Monte Carlo

OCTOBER 2, 2023

The data world has certainly benefited tremendously from open source solutions like Spark, dbt, and Airflow, but when it comes to data quality, it’s important to assess the pros and cons of open source data observability tools. That’s why data teams need to carefully evaluate their build vs. buy decisions.

Data Pipeline 52

Data Pipeline Machine Learning Data Data Science 52

Monte Carlo

FEBRUARY 7, 2023

At Monte Carlo, we like to think of data quality management within the context of physical fitness. No technology, including data observability , can act as a slimming belt toning your data quality while you lay back and relax. There is also a lot of bad data fitness advice.

Management 72

Management Data Data Pipeline Data Cleanse 72

Monte Carlo

AUGUST 31, 2023

Every data science team has that moment where it realizes it has outgrown its initial architecture. That moment came quickly for our team and our SQL-based feature store. Our codebase and data science team were growing rapidly in parallel as well. Here’s how and why we did it.

SQL 64

SQL Data Science Machine Learning Algorithm 64

Monte Carlo

MAY 31, 2023

Fundamentally, there are two different types of data teams in this worlds. This isn’t to say data teams should never resolve a ticket or field an ad-hoc request. Here are four ways I’ve seen data leaders seize that opportunity and make the transition from back office to front. The second is a value generator.

Data 59

Data BI Data Engineering Data Engineer 59

Monte Carlo

APRIL 26, 2022

What is DataOps? DataOps is a discipline that merges data engineering and data science teams to support an organization’s data needs, in a similar way to how DevOps helped scale software engineering. In this guide, we’ll explain each of the following: What is DataOps?

IT 64

IT Data Pipeline Data Engineering Data Engineer 64

Data Engineering Podcast

DECEMBER 25, 2022

Summary Five years of hosting the Data Engineering Podcast has provided Tobias Macey with a wealth of insight into the work of building and operating data systems at a variety of scales and for myriad purposes. Atlan is the metadata hub for your data ecosystem. Atlan is the metadata hub for your data ecosystem.

Building 100

Building Metadata Business Intelligence Data Lake 100

Knowledge Hut

FEBRUARY 6, 2024

DevOps is the practice of methodically monitoring numerous development-related areas, beginning with formulating an operation plan, carrying out development work involving integrating applications and testing, and finishing with deployment and operations. What is DevOps Monitoring?

Coding 52

Coding Systems Certification Designing 52

Monte Carlo

APRIL 24, 2023

In an evolving data landscape, the explosion of new tooling solutions—from cloud-based transforms to data observability —has made the question of “build versus buy” increasingly important for data leaders. Check out Part 1 of the build vs buy guide to catch up. Missed Nishith’s 5 considerations?

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Monte Carlo

SEPTEMBER 1, 2022

Data engineering is a relatively young profession, even for the tech space. While the role itself is rapidly evolving, the tooling, processes, and team structure are fragmented and amorphous at best. Simply put, data engineering time is a precious resource that needs to be invested wisely by both practitioners and data team leaders.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Monte Carlo

JUNE 12, 2023

We’ve seen it time and time again — change is the only constant for data teams. New customers hungry for data. New team structures to support them. And, occasionally, an entirely new data platform to meet evolving business needs. All while ensuring data reliability from end-to-end. Easy, right?

Kafka 52

Kafka Algorithm Data Pipeline High Quality Data 52

Knowledge Hut

JANUARY 10, 2024

A Scrum Master is a guide, facilitator and change agent and mentor who leads scrum teams in the right direction to ensure project success. Whereas a Business Analyst focuses on data collection and analysis and interpretation to make informed decisions, offer solutions and develop strategies to achieve project goals.

Business Analyst 52

Business Analyst Certification Project Data Analysis 52

François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. How do we build data products ? How can we interoperate between the data domains ?

Architecture 130

Architecture Technology Google Cloud Metadata 130

Monte Carlo

JULY 7, 2022

At the time, he was one of a very few people using the term “data contract.” Data contracts have since became one of the most discussed topics in data engineering. For posterity, we have preserved Barr’s forward that examines what was then a very nascent trend, but we have also added an updated data contract FAQ as an addendum.

Data Warehouse 52

Data Warehouse Software Engineer Software Engineering Data 52

Monte Carlo

AUGUST 25, 2023

Modern companies are ingesting, storing, transforming, and leveraging more data to drive more decision-making than ever before. Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs. But, the options for data storage are evolving quickly. Let’s dive in.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

MAY 17, 2023

Data observability, an organization’s ability to fully understand the health and quality of the data in their systems, has become one of the hottest technologies in modern data engineering. Table of Contents Core Data Observability Use Cases 1. Reduce The Amount Of Data Incidents 2.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52

Monte Carlo

MAY 17, 2023

Data observability, an organization’s ability to fully understand the health and quality of the data in their systems, has become one of the hottest technologies in modern data engineering. Table of Contents Core Data Observability Use Cases 1. Reduce the amount of data incidents 2.

Data Pipeline 52

Data Pipeline Data Data Engineering Data Engineer 52

Databand.ai

NOVEMBER 30, 2022

The Ravit Show Q&A: How More Data Observability Leads to Better Governance Ryan Yackel 2022-11-30 10:18:32 We recently had the opportunity to join an episode of The Ravit Show , a community for data science and AI professionals to upskill, grow, share, and learn from each other.

Government 52

Government Data Governance Architecture Google Cloud 52

Monte Carlo

NOVEMBER 14, 2023

Imagine, if you will, a world where data just… flows. This is the world that data orchestration tools aim to create. Data orchestration tools minimize manual intervention by automating the movement of data within data pipelines. So, what makes a good data orchestration tool? No hiccups.

Pipeline-centric 40

Pipeline-centric Google Cloud Data Workflow Python 40

Monte Carlo

SEPTEMBER 23, 2021

If your data breaks, does it make a sound? Nowadays, organizations ingest large amounts of data across increasingly complex ecosystems, and very often their data breaks silently, and as a result data teams are left in the dark – until it’s too late. Fortunately, data doesn’t have to be silent.

BI 52

BI Data Metadata Data Pipeline 52

Monte Carlo

DECEMBER 7, 2022

We sat down with Rob Parker, Senior Director of Data & Analytics, to understand how he applies this concept to his work building and scaling GitLab’s data platform with collaboration, scalability, and trust in mind. Rob was amazingly candid in sharing how his data team tackles complex problems at GitLab.

Building 52

Building Pipeline-centric Data Data Programming 52

Databand.ai

JULY 28, 2022

What is Data Lineage? Niv Sluzki 2022-07-28 10:20:02 The term “data lineage” has been thrown around a lot over the last few years. What started as an idea of connecting between datasets quickly became a very confusing term that now gets misused often. And getting it right matters even more to data organizations.

Metadata 52

Metadata Data Lake Datasets Data Warehouse 52

Databand.ai

JANUARY 24, 2023

What is DataOps? The Ultimate Guide for Data Teams Eric Jones 2023-01-24 12:21:38 If you find yourself hearing a lot about DataOps and then subsequently asking, “ What is DataOps? This guide details everything you need to know about DataOps, including: What is DataOps? What has led to the rise of DataOps?

Retail 52

Retail Banking Government Manufacturing 52

Grouparoo

OCTOBER 6, 2021

It was a fun experience and I think we made a good choice by picking 97 Things Every Data Engineer Should Know. This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

phData: Data Engineering

JANUARY 3, 2022

DataOps: What Is It, Core Principles, and Tools For Implementation Nick Goble January 3, 2022 When building a successful company, it’s critical to have a strategy around how you build and scale your business from a technology and data perspective. You can read the full guide without giving us your email — keep scrolling !)

IT 52

IT AWS Software Engineer Software Engineering 52

Monte Carlo

MAY 6, 2021

As data systems become increasingly distributed and companies ingest more and more data, the opportunity for error (and incidents) only increases. For decades, software engineering teams have relied on a multi-step process to identify, triage, resolve, and prevent issues from taking down their applications.

Management 40

Management Data Pipeline Software Engineer Software Engineering 40

Knowledge Hut

JANUARY 29, 2024

What is ITIL®? Today, the worlds of business and technology have overlapped each other and are linked inextricably. To thrive and to remain competitive, companies need to bring IT services in considerable focus. The transition of a company’s objectives and capabilities to IT can be an overwhelming process.

Certification 52

Certification Portfolio Designing Telecommunication 52

ProjectPro

NOVEMBER 30, 2021

If you are into Data Science or Big Data, you must be familiar with an ETL pipeline. This guide provides definitions, a step-by-step tutorial, and a few best practices to help you understand ETL pipelines and how they differ from data pipelines. How do we transform this data to get valuable insights from it?

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. What is ELT? ELT vs ETL.

Process 52

Process Building Raw Data Data Lake 52

AltexSoft

MARCH 2, 2023

As the amount of enterprise data continues to surge, businesses are increasingly recognizing the importance of data governance — the framework for managing an organization’s data assets for accuracy, consistency, security, and effective use. Projections show that the data governance market will expand from $1.81

Data Governance 52

Data Governance Government Healthcare Programming 52

AltexSoft

JUNE 26, 2023

All successful companies do it: constantly collect data. They track people’s behavior on the Internet, initiate surveys, monitor feedback, listen to signals from smart devices, derive meaningful words from emails, and take other steps to amass facts and figures that will help them make business decisions. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

JUNE 21, 2023

What is ADR? By keeping an eye on ADR, observing its fluctuations, and establishing pricing objectives considering the ADR trends, both hotels and vacation rentals can enhance revenue and improve their overall profitability. We also investigate predicting ADR through machine learning and strategies to enhance this KPI.

Hospitality 52

Hospitality Management Machine Learning Datasets 52

Cloudera

MAY 13, 2021

Since my last blog, What you need to know to begin your journey to CDP , we received many requests for a tool from Cloudera to analyze the workloads and help upgrade or migrate to Cloudera Data Platform (CDP). The good news is Cloudera has a tried and tested tool, Workload Manager (WM) that meets your needs.

Management 69

Management BI Data Warehouse Cloud 69

Confluent

SEPTEMBER 20, 2019

As a distributed system for collecting, storing, and processing data at scale, Apache Kafka ® comes with its own deployment complexities. In order to answer this question, let’s start by understanding what Apache Kafka in fact is. Description from the Apache Software Foundation about what Kafka is.

Kafka 21

Kafka Management Cloud AWS 21