Monte Carlo

JANUARY 23, 2024

I sat down with Maxime to discuss the current state of affairs, including the decentralization of the modern data stack, the fragmentation of the data team, the rise of the cloud, and how all these factors have changed the role of the data engineer forever. On the flipside, costs are more constrained. “It

Data Engineering 98

Data Engineering Data Engineer Engineering Data 98

Meltano

OCTOBER 5, 2022

DataOps engineers. Get Started With DataOps In this guide, we’ll explain all you need to know about a DataOps engineer, including their key responsibilities, and how these experts use a DataOps platform, like Meltano , to optimize internal processes. What Is A DataOps Engineer? How does this work?

Engineering 52

Engineering Raw Data Data Pipeline ETL Tools 52

Knowledge Hut

JANUARY 18, 2024

Proficiency in working with complex data sets, a deep understanding of AI and machine learning algorithms, and staying up-to-date on cloud-based analytics platforms, data privacy regulations, and emerging data sources are essential. Here are a few. Consequently, automation tools reduce manual effort and increase efficiency.

Data Analytics 52

Data Analytics Healthcare Machine Learning Algorithm 52

Christophe Blefari

DECEMBER 31, 2023

I also took part in my friend's podcast where we discussed 3 trends in data : data modeling, real-time analytics and DataOps. Octolis is a CDP / reverse-ETL solution and Brevo is a CRM, the join makes total sense. My retroprojective—a retro 2023 with a projection into 2024—will soon be written.

Data 100

Data Cloud Storage Datasets Python 100

Towards Data Science

JULY 24, 2023

A loud few have made headlines with a “cloud is expensive let’s go back to our server racks” movement. Data platforms with combined but decoupled storage and compute also provide a more robust, integrated user experience across several key dataops tasks. You see this same decision making paradigm playout with open-source solutions.

Metadata 96

Metadata Data Warehouse Data Lake Data Science 96

Data Engineering Podcast

JUNE 26, 2022

Unstruk is the DataOps platform for your unstructured data. Unstruk is the DataOps platform for your unstructured data. The options for ingesting, organizing, and curating unstructured files are complex, expensive, and bespoke. Unstruk Data is changing that equation with their platform approach to manage your unstructured assets.

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Datasets Unstructured Data Metadata MongoDB 130

Monte Carlo

AUGUST 31, 2023

Your CTO is excited about migrating to the cloud, and constantly sends your team articles highlighting performance measurements against some of the latest technologies. Over the past few years, more and more companies have been applying these concepts to data in the form of “DataOps.” We’ll dig into these questions next.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Data Engineering Podcast

JANUARY 23, 2022

In this episode Abhi Sivasailam shares his experience designing and implementing a data mesh solution with his team at Flexport, and the importance of defining and enforcing data contracts that are implemented at those domain boundaries. Go to dataengineeringpodcast.com/atlan today and sign up for a free trial.

Data Integration 100

Data Integration Data Pipeline Data Architecture 100

Cloudera

SEPTEMBER 15, 2022

Modern data platforms deliver an elastic, flexible, and cost-effective environment for analytic applications by leveraging a hybrid, multi-cloud architecture to support data fabric, data mesh, data lakehouse and, most recently, data observability. Ramsey International Modern Data Platform Architecture. What is a data mesh?

Data Lake 79

Data Lake Analytics Application Cloud Storage Architecture 79

DataKitchen

JANUARY 18, 2023

While you’re admiring the latest cloud tech, don’t forget that humans have been debugging pipelines, at least since the Romans built the aqueducts. That’s why a key goal of DataOps is to expose your best-laid plans to real-life urgencies faster and initiate that crucial feedback loop sooner. I won’t get into it.

Data Pipeline 52

Data Pipeline Data AWS Data Engineering 52

DataKitchen

OCTOBER 28, 2021

Engineers unleashed artificial intelligence (AI) bias, and it will be engineers who design the solutions that eliminate it. The global AI market is projected to grow at a compound annual growth rate (CAGR) of 33% through 2027 , drawing upon strength in cloud-computing applications and the rise in connected smart devices. Chris Bergh.

Coding 52

Coding IT Manufacturing Algorithm 52

Data Engineering Podcast

DECEMBER 7, 2020

How much time could you save if those tasks were automated across your cloud platforms? Immuta is an automated data governance solution that enables safe and easy data analytics in the cloud. How much time could you save if those tasks were automated across your cloud platforms?

Building 100

Building Consulting Big Data Data Engineering 100

Data Engineering Podcast

NOVEMBER 23, 2020

Summary One of the oldest aphorisms about data is "garbage in, garbage out", which is why the current boom in data quality solutions is no surprise. How much time could you save if those tasks were automated across your cloud platforms? How much time could you save if those tasks were automated across your cloud platforms?

Hadoop 100

Hadoop Data Pipeline BI Data 100

Monte Carlo

SEPTEMBER 12, 2023

The current data stack As an AWS shop, the key components of the Whatnot data stack include Snowflake, dbt Cloud for transformation, Dagster for orchestration, Segment as a customer data platform, Confluent for managed Kafka, Rockset for real time aggregations, and Sigma+Hex for presentation.

Machine Learning 52

Machine Learning Data Entertainment SQL 52

Monte Carlo

AUGUST 10, 2023

In this post, I’ll cover: Data observability is as essential to DataOps as observability is to DevOps Why is data observability important? Now let’s calculate its cost, and thus the value of a data observability solution. This allows the data observability solution to be performant, scalable and cost-efficient.

Data Pipeline 98

Data Pipeline Software Engineer Software Engineering Machine Learning 98

Meltano

OCTOBER 5, 2022

Plus, we’ll explain how data engineers use Meltano, our DataOps platform, for efficient data management. However, to do their jobs well, data engineers require proper tools and solutions to facilitate the extraction of data from multiple sources. Interested in a data platform? What Is Data Engineering?

Data Engineering 52

Data Engineering Data Engineer Engineering Raw Data 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. What Are The Components of a DataOps Strategy? Want to Save This eBook for Later?

IT 52

IT AWS Software Engineer Software Engineering 52

Monte Carlo

JULY 18, 2023

In This Article: The storage and compute data platform spectrum Challengers Platforms Degree and purpose of consolidation Performance vs ease of use In defense of the MDS The storage and compute data platform spectrum A loud few have made headlines with a “cloud is expensive let’s go back to our server racks” movement.

Metadata 52

Metadata Data Warehouse Data Lake Government 52

Big Data Tools

OCTOBER 10, 2022

Apache Pegasus 2.3.0 – Have you ever been in a situation where you were designing a storage architecture and all the solutions in some areas just seemed wrong, leaving you to choose between an unsuitable option and an even less suitable one? If we use cloud providers, we don’t have to think about that. Cloudstack 4.17.1.0 (LTS)

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

Big Data Tools

OCTOBER 10, 2022

Apache Pegasus 2.3.0 – Have you ever been in a situation where you were designing a storage architecture and all the solutions in some areas just seemed wrong, leaving you to choose between an unsuitable option and an even less suitable one? If we use cloud providers, we don’t have to think about that. Cloudstack 4.17.1.0 (LTS)

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

Monte Carlo

JUNE 22, 2023

Here are the session takeaways: Roche , is one of the world’s largest biotech companies, as well as a leading provider of in-vitro diagnostics and a global supplier of transformative innovative solutions across major disease areas. This is where solutions like Monte Carlo, Immuta, Collibra, and Data Mesh Design Studio come into play.

Building 52

Building Data Ingestion Data Business Analyst 52

Precisely

JUNE 26, 2023

Forward-thinking businesses invest in digital transformation, cloud adoption, advanced analytics and predictive modeling, and supply chain resiliency. And technology is what helps you achieve that agility so you can not only survive, but thrive – building competitive advantage and driving long-term success. The biggest surprise?

Data Integration 52

Data Integration Data Cleanse Data Governance Data Programming 52

François Nguyen

MARCH 7, 2021

The solution could be tempting to have only one team working on one data platform. Even without any technology, at the end, people will use Excel or any other solution to fulfill their needs. But you can see it too as a Data Strategist who will translate business problems to analytical solutions and start to think data as a product.

Government 130

Government Data Governance Data Metadata 130

Monte Carlo

JULY 18, 2023

In This Article: The storage and compute data platform spectrum Challengers Platforms Degree and purpose of consolidation Performance vs ease of use In defense of the MDS The storage and compute data platform spectrum A loud few have made headlines with a “cloud is expensive let’s go back to our server racks” movement.

Metadata 40

Metadata Data Warehouse Data Lake Government 40

Ascend.io

MARCH 2, 2023

“But we also had over 75 projects orchestrated with Airflow and a combination of tools, cloud services, and bespoke code. Terry Dougal Intelligent Data Pipelines at Audacy Instead of hiring more data engineers to patch over all the tooling with more bespoke code, Terry shifted gears and looked for a new solution.

Data Pipeline 52

Data Pipeline Media Portfolio Data Ingestion 52

dbt Developer Hub

JULY 2, 2023

Due to its complexity, Data Vault is not a go-to choice for: Simple and constant systems; Quick one-off solutions for experiments or short-term data warehouse projects; Data warehouse layers needed for direct reporting. In addition to its own capabilities, dbt Cloud features enhance this advantage even further.

Cloud 52

Cloud Data Warehouse Data BI 52

Databand.ai

DECEMBER 13, 2022

Follow Charles on LinkedIn 3) Deepak Goyal Azure Instructor at Microsoft Deepak is a certified big data and Azure Cloud Solution Architect with more than 13 years of experience in the IT industry. Caleb has over a decade of experience in the data and engineering space, currently working as a solutions architect at Elastic.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Monte Carlo

FEBRUARY 23, 2023

We had been in the cloud for years, which helped some. DataOps tweaks DevOps methodology as data observability does to observability. Remember, as the opening anecdote and J-Kidd’s snapped ligaments illustrated, the elasticity of the cloud is not a cure-all. A powerful surge of traffic is inevitable. Data is different.

Data Engineering 98

Data Engineering Data Engineer Engineering Software Engineer 98

Towards Data Science

FEBRUARY 24, 2023

We had been in the cloud for years, which helped some. DataOps tweaks DevOps methodology as data observability does to observability. Remember, as the opening anecdote and J-Kidd’s snapped ligaments illustrated, the elasticity of the cloud is not a cure-all. A powerful surge of traffic is inevitable. Data is different.

Data Engineering 97

Data Engineering Data Engineer Engineering Software Engineer 97

Ascend.io

MARCH 2, 2023

“But we also had over 75 projects orchestrated with Airflow and a combination of tools, cloud services, and bespoke code. Terry Dougal Intelligent Data Pipelines at Audacy Instead of hiring more data engineers to patch over all the tooling with more bespoke code, Terry shifted gears and looked for a new solution.

Data Pipeline 52

Data Pipeline Media Portfolio Data Ingestion 52

Ascend.io

JULY 28, 2023

This includes mature access controls, CRUD controls, sharing controls, integration of DataOps into CI/CD workflows, and usability by differently skilled team members. Resources: Eventually, different data pipelines will perform better in different infrastructure environments, because different clouds provide different services.

Data Pipeline 52

Data Pipeline Architecture Lambda Architecture Data Architecture 52

Monte Carlo

FEBRUARY 8, 2024

In this post, we will share analyst reports and the core evaluation criteria we see organizations use when ranking data observability solutions. If a solution does not have features covering these five pillars then it cannot be considered a data observability tool. Cloud-native solutions often have a leg up here.

BI 59

BI Data Pipeline Data Warehouse Data 59

Pipeline Data Engineering

NOVEMBER 9, 2021

Clouds and virtualisation? Recommendations for diving deeper into ML, data modeling and dataops? What would you say if I told you that the assignments at Pipeline Academy are designed in a technology-agnostic and solution-oriented fashion? Real-life coding challenges from renowned organisations? It's all in our curriculum.

Data Engineering 52

Data Engineering Data Engineer Engineering BI 52

Monte Carlo

NOVEMBER 21, 2022

Prediction #1: Cloud Manages 75% Of All Data Workloads by 2024 (Tomasz) Image courtesy of Tomasz Tunguz. This was Tomasz’s first prediction , and based on an analyst report earlier this year showing the growth of cloud versus on-premises RDBMS revenue. Snowflake went from a hundred million in revenue to about 1.2

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Monte Carlo

DECEMBER 7, 2022

The GitLab data stack Using a cloud-based and modular data stack makes it easy for the data team to scale while serving distributed stakeholders. We’ve been able to move away from being the typical order taker into being a trusted business partner in the journey of building scalable and reliable solutions for the business.”

Building 52

Building Pipeline-centric Data Data Programming 52

Grouparoo

OCTOBER 6, 2021

90 What to Do When You Don’t Get Any Credit To get credit, talk in terms of business value, not technology 91 When Our Data Science Team Didn’t Produce Value Balance long-term solutions with short-term needs 92 When to Avoid the Naive Approach Storage format and schema are good to get right from the beginning. Just get the job done.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

DataKitchen

APRIL 13, 2021

Download the 2021 DataOps Vendor Landscape here. DataOps is a hot topic in 2021. This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. As a result, vendors that market DataOps capabilities have grown in pace with the popularity of the practice.

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Consulting Machine Learning Data Science Data Pipeline 123