Precisely

MAY 13, 2024

Key Takeaways: Data integration is vital for real-time data delivery across diverse cloud models and applications, and for leveraging technologies like generative AI. As enterprise technology landscapes grow more complex, the role of data integration is more critical than ever before.

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

Netflix Tech

MARCH 10, 2023

Studio applications use this service to store their media assets, which then goes through an asset cycle of schema validation, versioning, access control, sharing, triggering configured workflows like inspection, proxy generation etc. This pattern grows over time when we need to access and update the existing assets metadata.

Management 94

Management Kafka Metadata Media 94

Data Engineering Podcast

FEBRUARY 19, 2023

Summary Cloud data warehouses have unlocked a massive amount of innovation and investment in data applications, but they are still inherently limiting. Because of their complete ownership of your data they constrain the possibilities of what data you can store and how it can be used. We feel your pain.

IT 147

IT Data Lake Metadata Data Warehouse 147

Knowledge Hut

MARCH 7, 2024

The year 2024 saw some enthralling changes in volume and variety of data across businesses worldwide. The surge in data generation is only going to continue. Foresighted enterprises are the ones who will be able to leverage this data for maximum profitability through data processing and handling techniques.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

Snowflake

JULY 10, 2023

Announced at Summit, we’ve recently added to Snowpark the ability to process files programmatically, with Python in public preview and Java generally available. Data engineers and data scientists can take advantage of Snowflake’s fast engine with secure access to open source libraries for processing images, video, audio, and more.

Unstructured Data 40

Unstructured Data Python Process Scala 40

Data Engineering Weekly

MARCH 24, 2024

link] Kai Waehner: The Data Streaming Landscape 2024 This is a comprehensive overview of the state of the data streaming landscape in 2024. As we predicted in the key trends of 2023 about Apache Flink as a clear winner in the stream processing frameworks, we see Confluent offering Flink as a service.

Data Engineering 62

Data Engineering Data Engineer Engineering Metadata 62

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. Searching for data Imagine being a data engineer/analyst tasked with identifying the top-selling products within your company.

Systems 76

Systems Raw Data Metadata Data Cleanse 76

Christophe Blefari

FEBRUARY 3, 2023

Delivering the data news ( credits ) Hey you, it's already February. The article shows our Netflix art creators are using past data to create new artworks. ebay, Variable Hub a data access layer for risk decisioning — Looks like a feature store but for risk topics. Every week same analysis for me.

BI 130

BI Google Cloud SQL Machine Learning 130

The Modern Data Company

APRIL 15, 2024

The elegance of Data Products is undeniable, but many leaders question the efficacy of their data strategies: Why does the return on data investments often disappoint? Why is proving data’s value becoming harder? Why do data models become more cumbersome than beneficial? What Exactly Is a Data Product?

Government 52

Government Metadata Data Data Lake 52

Data Engineering Podcast

AUGUST 28, 2022

For data engineers, this is a monumental undertaking. 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. The only thing worse than having bad data is not knowing that you have it.

Data Engineering 100

Data Engineering Data Engineer MongoDB Metadata 100

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Metadata layer 4. API layer 5.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 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 ?

Technology 130

Technology Architecture Google Cloud Metadata 130

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Metadata layer 4. API layer 5.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Data Engineering Podcast

AUGUST 6, 2022

Summary Data mesh is a frequent topic of conversation in the data community, with many debates about how and when to employ this architectural pattern. The team at AgileLab have first-hand experience helping large enterprise organizations evaluate and implement their own data mesh strategies.

Metadata 100

Metadata MongoDB MySQL Business Intelligence 100

ThoughtSpot

MAY 31, 2023

With the recent announcement of ThoughtSpot Sage , we launched a number of enhancements to our search capabilities including AI-generated answers, AI-powered search suggestions, and AI-assisted data modeling. In this article we will walk you through the steps we take to secure your data during the LLM interaction.

Data Security 86

Data Security Metadata Transportation Data Warehouse 86

Netflix Tech

NOVEMBER 14, 2023

In the previous installments of this series, we introduced Psyberg and delved into its core operational modes: Stateless and Stateful Data Processing. Pipelines After Psyberg Let’s explore how different modes of Psyberg could help with a multistep data pipeline. Audit Run various quality checks on the staged data.

Metadata 97

Metadata Data Pipeline Scala Data Workflow 97

LinkedIn Engineering

DECEMBER 19, 2023

Co-authors: Arjun Mohnot , Jenchang Ho , Anthony Quigley , Xing Lin , Anil Alluri , Michael Kuchenbecker LinkedIn operates one of the world’s largest Apache Hadoop big data clusters. Historically, deploying code changes to Hadoop big data clusters has been complex.

Big Data 92

Big Data Hadoop Metadata Data 92

Precisely

JUNE 6, 2023

At Precisely’s Trust ’23 conference, Chief Operating Officer Eric Yau hosted an expert panel discussion on modern data architectures. The group kicked off the session by exchanging ideas about what it means to have a modern data architecture. Conventional architectures simply cannot deliver that because they’re too rigid.

Data Architecture 52

Data Architecture Architecture Metadata Data Lake 52

Ascend.io

FEBRUARY 28, 2024

The rise of generative AI is changing more than just technology; it’s reshaping our professional landscapes — and yes, data engineering is directly experiencing the impact. How does AI recalibrate the workload and priorities of data teams? How can data engineers harness the power of AI?

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Data Engineering Weekly

DECEMBER 29, 2022

Data catalogs are the most expensive data integration systems you never intended to build. Data Catalog as a passive web portal to display metadata requires significant rethinking to adopt modern data workflow, not just adding “modern” in its prefix. How happy are you with your data catalogs?

Metadata 62

Metadata Data Warehouse ETL Tools Data Workflow 62

Data Engineering Weekly

JUNE 29, 2023

But hey, I met my friends after a long time and got my copy of “ Fundamentals of Data Engineering ” signed by Joe Reis & Matt Housely. If you’re starting data engineering, I highly recommend reading it. There are many exciting announcements from both the data conferences, and I want to highlight a few themes here.

Data Engineering 76

Data Engineering Data Engineer Google Cloud Engineering 76

Precisely

MAY 31, 2023

To innovate, compete, and grow in the current macroeconomic environment, enterprises must approach data strategically. A sound data strategy doesn’t happen by accident; it’s built on a foundation of data integrity , including accuracy, consistency, and rich context. Many organizations still struggle with data integrity.

Data Integration 52

Data Integration Metadata Data Governance Data 52

Monte Carlo

MAY 18, 2023

Data lineage tools are like detectives that help data professionals quickly sort through the tangled webs of interdependencies that make up the modern data stack. The first instinct of many early stage companies or budget strapped data teams is to turn to open source data lineage tools.

Metadata 64

Metadata Data Lake Government Data Governance 64

Towards Data Science

MAY 7, 2024

meetings with sales reps from all of the SaaS data integration tooling companies and are granted 14 day access to try their wares. If you have a favorite way to test out new data tools, add them to the comments! If you have a favorite way to test out new data tools, add them to the comments!

ETL Tools 77

ETL Tools Metadata Data Integration Data Science 77

Data Engineering Weekly

MARCH 10, 2024

Editor’s Note: Chennai Meetup Wrap-Up & Preparation work started for DEWCon I am so grateful for the enthusiastic participants who made our Chennai Data Heroes- Community for Data Folks meetup vibrant! Big thanks to our insightful speakers, Hareshkumar Selvakumar - Talks about his work on Data Products for PayPal.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Cloudera

MARCH 3, 2022

Whether the enterprise uses dozens or hundreds of data sources for multi-function analytics, all organizations can run into data governance issues. Bad data governance practices lead to data breaches, lawsuits, and regulatory fines — and no enterprise is immune. . Everyone Fails Data Governance. In 2019, the U.K.’s

Data Governance 100

Data Governance Government Metadata Medical 100

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

Cloudera

DECEMBER 10, 2020

Why worry about costs with cloud-native data warehousing? Have you been burned by the unexpected costs of a cloud data warehouse? If not, before adopting a cloud data warehouse, consider the true costs of a cloud-native data warehouse. These costs impede the adoption of cloud-native data warehouses.

Data Warehouse 98

Data Warehouse Cloud Storage Metadata Data 98

Towards Data Science

DECEMBER 1, 2023

Pet Project for Data/Analytics Engineers: Explore Modern Data Stack Tools — dbt Core, Snowflake, Fivetran, GitHub Actions. This hands-on experience will allow you to develop an end-to-end data lifecycle, from extracting data from your Google Calendar to presenting it in a Snowflake analytics dashboard. See Github repo.

Data Engineering 67

Data Engineering Data Engineer Project Engineering 67

Snowflake

APRIL 29, 2024

Recover: establish processes for rapid recovery after incidents to ensure business continuity. This translates to several key requirements and their associated benefits: More stringent technical and process-oriented security measures, enhancing protection for both FEs and their ICT third-party providers. or better) for data in transit.

Transportation 84

Transportation Data Governance Government Consulting 84

Precisely

JULY 21, 2023

Organizations face increasing demands for real-time processing and analysis of large volumes of data. Used by more than 75% of the Fortune 500, Apache Kafka has emerged as a powerful open source data streaming platform to meet these challenges. This is where Confluent steps in.

Data Integration 52

Data Integration Kafka Bytes Banking 52

AltexSoft

FEBRUARY 11, 2023

Data is now one of the most valuable assets for any kind of business. The 11th annual survey of Chief Data Officers (CDOs) and Chief Data and Analytics Officers reveals 82 percent of organizations are planning to increase their investments in data modernization in 2023. What is a data architect?

Data Architect 87

Data Architect Certification Generalist Big Data 87

Databand.ai

JULY 19, 2023

Data Lineage Tools: Key Capabilities and 5 Notable Solutions Ryan Yackel July 19, 2023 What Are Data Lineage Tools? Data lineage tools provide a visual representation of your data’s journey across multiple systems and transformations. Data lineage tools are not a new concept.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

Cloudera

MARCH 14, 2023

We just announced the general availability of Cloudera DataFlow Designer , bringing self-service data flow development to all CDP Public Cloud customers. In this blog post we will put these capabilities in context and dive deeper into how the built-in, end-to-end data flow life cycle enables self-service data pipeline development.

Data Pipeline 84

Data Pipeline Designing Kafka Metadata 84

Ascend.io

APRIL 19, 2023

The “modern data stack” has become increasingly prominent in recent years, promising a streamlined approach to data processing. Where did the modern data stack come from? The modern data stack emerged as a response to a glaring gap in the data ecosystem: a dearth of developer tools.

Metadata 52

Metadata Business Analyst Hadoop Software Engineer 52

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52