Christophe Blefari

JANUARY 20, 2024

You'll be also asked to put in place a data infrastructure. It means a data warehouse, a data lake or other concepts starting with data. Read technical blogs, watch conferences and read 📘 Designing Data-Intensive Applications (even if it could be overkill). Is it really modern?

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Data Engineering Podcast

SEPTEMBER 4, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. RudderStack helps you build a customer data platform on your warehouse or data lake.

IT 100

IT Metadata MongoDB MySQL 100

Data Engineering Podcast

DECEMBER 4, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. Data engineers don’t enjoy writing, maintaining, and modifying ETL pipelines all day, every day.

Business Intelligence 100

Business Intelligence Metadata BI MongoDB 100

Data Engineering Podcast

DECEMBER 19, 2021

Summary Building a well managed data ecosystem for your organization requires a holistic view of all of the producers, consumers, and processors of information. The team at Metaphor are building a fully connected metadata layer to provide both technical and social intelligence about your data.

Systems 100

Systems Building Metadata Data Warehouse 100

Data Engineering Weekly

MARCH 24, 2024

Dive into Spyne's experience with: - Their search for query acceleration with pre-aggregations and caching - Developing new functionality with Open AI - Optimizing query cost with their data warehouse [link] Suresh Hasuni: Cost Optimization Strategies for Scalable Data Lakehouse Cost is the major concern as the adoption of data lakes increases.

Data Engineering 62

Data Engineering Data Engineer Engineering Metadata 62

Data Engineering Podcast

MARCH 27, 2022

Acryl Data provides DataHub as an easy to consume SaaS product which has been adopted by several companies. Signup for the SaaS product at dataengineeringpodcast.com/acryl RudderStack helps you build a customer data platform on your warehouse or data lake. Can you explain how the Privacera platform is architected?

Data Governance 130

Data Governance Government Cloud Building 130

The Modern Data Company

APRIL 15, 2024

The term “Data Product” has become a buzzword, often misused or overstretched. But at its core, a Data Product is much more than just data. This blend ensures that a Data Product is informative, actionable, and adaptable to various needs.

Government 52

Government Metadata Data Data Lake 52

Ascend.io

AUGUST 31, 2023

Secondly , the rise of data lakes that catalyzed the transition from ELT to ELT and paved the way for niche paradigms such as Reverse ETL and Zero-ETL. Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 89

Data Lake Data Warehouse BI SQL 89

Monte Carlo

JUNE 28, 2022

To help organizations realize the full potential of their data lake and lakehouse investments, Monte Carlo, the data observability leader, is proud to announce integrations with Delta Lake and Databricks’ Unity Catalog for full data observability coverage. billion in 2020 to 17.60 billion in 2020 to 17.60

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52

Monte Carlo

FEBRUARY 21, 2023

Despite its prevalence, data can be messy, siloed, ungovernable, and inaccessible—especially to the non-technical employees who rely on it. Enter data fabric: a data management architecture designed to serve the needs of the business, not just those of data engineers. Table of Contents What is a data fabric?

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

Despite its prevalence, data can be messy, siloed, ungovernable, and inaccessible—especially to the non-technical employees who rely on it. Enter data fabric: a data management architecture designed to serve the needs of the business, not just those of data engineers. Table of Contents What is a data fabric?

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Towards Data Science

FEBRUARY 6, 2024

ERP and CRM systems are designed and built to fulfil a broad range of business processes and functions. This generalisation makes their data models complex and cryptic and require domain expertise. This means that we need to expose global identifiers so our data product might be universally used in other domains.

Systems 86

Systems Raw Data Metadata Data Cleanse 86

Monte Carlo

MAY 18, 2023

We’ve been open about this work, providing very technical deep dives into how we developed column-level lineage and even some of our failures in building Spark data lineage for data lakes. The Spark data lake lineage example is helpful for context here. These features make it useful for managing data lineage.

Metadata 64

Metadata Data Lake Government Data Governance 64

Data Engineering Podcast

MARCH 22, 2021

How does CDC fit into a broader data platform, particularly where there are likely to be other data integration pipelines in operation? Fivetran/Airbyte/Meltano/custom scripts) What are the moving pieces in a CDC workflow that need to be considered as you are designing the system? S3/Parquet or Trino/Drill/etc.)

Data Warehouse 100

Data Warehouse Metadata Data Lake Hadoop 100

Grouparoo

OCTOBER 6, 2021

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. For example, grouping the ones about metadata, discoverability, and column naming might have made a lot of sense.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Data Engineering Podcast

SEPTEMBER 23, 2018

Using the metaphor of a museum curator carefully managing the precious resources on display and in the vaults, he discusses the various layers of an enterprise data strategy. Can you walk through the stages of an ideal lifecycle for data within the context of an organizations uses for it?

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

Data Engineering Podcast

APRIL 24, 2022

Acryl Data provides DataHub as an easy to consume SaaS product which has been adopted by several companies. Signup for the SaaS product at dataengineeringpodcast.com/acryl RudderStack helps you build a customer data platform on your warehouse or data lake. Can you describe how Whylogs is implemented?

Machine Learning 100

Machine Learning Systems Data Lake Metadata 100

Data Engineering Podcast

NOVEMBER 20, 2021

In the same way that application performance monitoring ensures reliable software and keeps application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines. Start trusting your data with Monte Carlo today! How has that shifted the way that engineers approach pipeline design and composition?

Data Warehouse 100

Data Warehouse Data Lake BI Business Intelligence 100

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. But first, let’s define the data mesh design pattern. The past decades of enterprise data platform architectures can be summarized in 69 words.

Pharmaceutical 98

Pharmaceutical Data Lake Data Architecture Scala 98

Rockset

APRIL 26, 2023

In part 1 , we covered the technology landscape for real-time analytics on streaming data. In this post, we’ll get to the details: how does one design an RTA system? Offline feature store : Detecting anomalies requires historical data in order to have a baseline for comparisons. The database has two primary jobs.

Architecture 52

Architecture Transportation Data Lake Insurance 52

Hepta Analytics

FEBRUARY 14, 2022

We already had a script that downloaded a csv file, processed the data and pushed the data to postgres database. This week, we got to think about our data ingestion design. When the business intelligence needs change, they can go query the raw data again. The purpose of the data is not determined.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Data Engineering Weekly

JANUARY 6, 2023

Author: Chris Ricommni Recap Github: [link] [Don't forget to star it] I’m excited to release Recap , a dead simple data catalog for engineers written in Python. Recap makes it easy for engineers to build infrastructure and tools that need metadata. Unlike traditional data catalogs, Recap is designed to power software.

Metadata 40

Metadata ETL Tools MySQL Data Lake 40

Data Engineering Podcast

AUGUST 6, 2022

RudderStack helps you build a customer data platform on your warehouse or data lake. Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control.

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

AltexSoft

FEBRUARY 11, 2023

In the article, we explore the role of a data architect, discuss the responsibilities and required skills, and share what kind of companies may need such a specialist. What is a data architect? Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Cloudera

JANUARY 19, 2022

Cloudera Data Platform (CDP) scored among the top 10 vendors on all four Analytical Use Cases — Data Warehouse, Logical Data Warehouse, Data Lake and Operational Intelligence in the Critical Capabilities for Cloud Database Management Systems for Analytics Use Cases.

Database 86

Database Cloud Data Warehouse Data Lake 86

Workfall

JUNE 12, 2023

CDC also plays a crucial role in data integration and ETL processes. It captures incremental changes from transactional databases or other sources, efficiently loading them into data warehouses or data lakes. It is commonly employed for compliance monitoring, data lineage, and maintaining historical records.

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

Monte Carlo

MARCH 3, 2021

Our SOC 2 designation means that Monte Carlo has designed a set of internal controls, systems, policies, and procedures that meet industry best practices for protecting our customer data. Specifically, with Monte Carlo, data never leaves your environment — full stop. What does this mean for you?

Metadata 52

Metadata Data Lake Business Intelligence Certification 52

Data Engineering Podcast

JUNE 19, 2022

Summary Metadata is the lifeblood of your data platform, providing information about what is happening in your systems. In order to level up their value a new trend of active metadata is being implemented, allowing use cases like keeping BI reports up to date, auto-scaling your warehouses, and automated data governance.

Metadata 130

Metadata MongoDB Scala MySQL 130

Ascend.io

MAY 23, 2023

Already in 2016, IBM estimated the cost of bad data to be over three trillion dollars, and that was before the chaos of data lakes emerged and orphaned datasets began to swamp the land. This strategy minimizes clutter and storage space, but could lose some data that is no longer useful going forward.

Datasets 52

Datasets Data Pipeline Metadata Database 52

Cloudera

SEPTEMBER 15, 2022

The gathering in 2022 marked the sixteenth year for top data and analytics professionals to come to the MIT campus to explore current and future trends. A key area of focus for the symposium this year was the design and deployment of modern data platforms.

Data Lake 78

Data Lake Analytics Application Cloud Storage Architecture 78

Databand.ai

AUGUST 30, 2023

Faster data processing: By automating data workflows and leveraging modern data processing technologies, DataOps architecture accelerates data ingestion, transformation, and analysis. They include the various databases, applications, APIs, and external systems from which data is collected and ingested.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Netflix Tech

MARCH 7, 2024

The Machine Learning Platform (MLP) team at Netflix provides an entire ecosystem of tools around Metaflow , an open source machine learning infrastructure framework we started, to empower data scientists and machine learning practitioners to build and manage a variety of ML systems.

Systems 90

Systems Media Machine Learning Data Warehouse 90

ProjectPro

JANUARY 24, 2023

Azure Data Factory is a cloud-based data integration tool that lets you build data-driven processes in the cloud to orchestrate and automate data transfer and transformation. ADF itself does not save any data. Both services support structured and unstructured data.

AWS 52

AWS Cloud Amazon Web Services ETL Tools 52

Silectis

JANUARY 3, 2021

Data Architecture Data architecture is a composition of models, rules, and standards for all data systems and interactions between them. Data Catalog An organized inventory of data assets relying on metadata to help with data management.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

SEPTEMBER 29, 2023

Azure Data Engineer Certification Cost DP 203 exam Cost : $165 Exam Details Exam Duration: 150 minutes Number of questions: 40 to 60 Passing Marks: 700/1000 Exam syllabus: When it comes to the way it designs its exams, Microsoft is incredibly open. Then, you can create analytical layer serving designs.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Monte Carlo

AUGUST 25, 2023

That’s why it’s essential for teams to choose the right architecture for the storage layer of their data stack. But, the options for data storage are evolving quickly. Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52