Ascend.io

MAY 7, 2024

” Key Partnership Benefits: Cost Optimization and Efficiency : The collaboration is poised to reduce IT and data management costs significantly, including an up to 68% reduction in data stack spend and the ability to build data pipelines 7.5x ABOUT ASCEND.IO

Pipeline-centric 52

Pipeline-centric Data Cleanse Data Security Data Pipeline 52

Data Engineering Weekly

MARCH 3, 2024

link] Zendesk: dbt at Zendesk The Zendesk team shares their journey of migrating legacy data pipelines to dbt, focusing on making them more reliable, efficient, and scalable. The article also highlights sink-specific improvements and operator-specific enhancements that contribute to the overall performance boost.

Data Engineering 67

Data Engineering Data Engineer Pipeline-centric Engineering 67

AltexSoft

FEBRUARY 11, 2023

To get a better understanding of a data architect’s role, let’s clear up what data architecture is. Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. What is the main difference between a data architect and a data engineer?

Data Architect 87

Data Architect Certification Generalist Big Data 87

Data Engineering Weekly

FEBRUARY 25, 2024

Key application areas included catalog enrichment, review summarization, and neural search, with a strategic approach to managing risks and responsibly leveraging AI's potential. This initiative reduced costs and enhanced computational efficiency, demonstrating the significant benefits of GPUs in big data environments.

Data Engineering 62

Data Engineering Data Engineer Engineering Kafka 62

Monte Carlo

APRIL 4, 2023

Data mesh vs data warehouse is an interesting framing because it is not necessarily a binary choice depending on what exactly you mean by data warehouse (more on that later). Despite their differences, however, both approaches require high-quality, reliable data in order to function.

Data Warehouse 52

Data Warehouse Data Governance Data Architecture 52

Cloudera

DECEMBER 1, 2022

Full-stack observability is a critical requirement for effective modern data platforms to deliver the agile, flexible, and cost-effective environment organizations are looking for. RI is a global leader in the design and deployment of large-scale, production-level modern data platforms for the world’s largest enterprises.

Data Lake 83

Data Lake Data Pipeline Data Governance Analytics Application 83

Knowledge Hut

JANUARY 18, 2024

Automation and DataOps for Improved Data Analytics Automation and DataOps (Data Operations) are emerging technologies that improve data analytics by streamlining and automating various tasks involved in the data pipeline. Consequently, automation tools reduce manual effort and increase efficiency.

Data Analytics 52

Data Analytics Healthcare Machine Learning Algorithm 52

Striim

NOVEMBER 8, 2023

” Self-serve data infrastructure as a platform The principle of creating a self-serve data infrastructure is to provide tools and user-friendly interfaces so that generalist developers (and non-technical people) can quickly get access to data or develop analytical data products speedily and seamlessly.

Architecture 52

Architecture Generalist Government Datasets 52

Precisely

MARCH 14, 2023

We optimize these products for use cases and architectures that will remain business-critical for years to come. Instead of moving customer data to the processing engine, we move the processing engine to the data. Manage data with a seamless, consistent design experience – no need for complex coding or highly technical skills.

Data Integration 52

Data Integration High Quality Data BI Data 52

Cloudera

MARCH 23, 2022

In fact, we recently announced the integration with our cloud ecosystem bringing the benefits of Iceberg to enterprises as they make their journey to the public cloud, and as they adopt more converged architectures like the Lakehouse. Simplify data management . 1: Multi-function analytics . The *Any*-house.

Metadata 90

Metadata Data Architecture BI Machine Learning 90

Cloudera

OCTOBER 7, 2021

The concept of the data mesh architecture is not entirely new; Its conceptual origins are rooted in the microservices architecture, its design principles (i.e., need to integrate multiple “point solutions” used in a data ecosystem) and organization reasons (e.g., Components of a Data Mesh.

Architecture 124

Architecture Metadata Government Kafka 124

Cloudera

FEBRUARY 22, 2021

The Cloudera Data Platform (CDP) represents a paradigm shift in modern data architecture by addressing all existing and future analytical needs. Cloudera Data Catalog (part of SDX) replaces data governance tools to facilitate centralized data governance (data cataloging, data searching / lineage, tracking of data issues etc. ).

Data Warehouse 79

Data Warehouse Data Governance Government Cloud 79

Monte Carlo

AUGUST 31, 2023

As the data analyst or engineer responsible for managing this data and making it usable, accessible, and trustworthy, rarely a day goes by without having to field some request from your stakeholders. But what happens when the data is wrong? In our opinion, data quality frequently gets a bad rep.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

DataKitchen

JANUARY 23, 2023

Data lineage can also be used for compliance, auditing, and data governance purposes. DataOps Observability Five on data lineage: Data lineage traces data’s origin, history, and movement through various processing, storage, and analysis stages. What is missing in data lineage?

Data Governance 52

Data Governance Government Data Pipeline Data 52

Databand.ai

JANUARY 24, 2023

DataOps is an automated, process-oriented methodology used by analytics and data teams to improve quality and reduce the cycle times of data and analytics. The goal of DataOps is to deliver value faster by creating predictable delivery and change management of data, data models, and related artifacts.”

Retail 52

Retail Banking Government Manufacturing 52

Monte Carlo

DECEMBER 8, 2023

While both data provenance vs. data lineage are mechanisms for understanding data at early stages, they differ in use cases. Data provenance is useful for validating and auditing data. Data lineage is useful for optimizing and troubleshooting data pipelines. Data lineage diagram.

Metadata 52

Metadata Data Data Warehouse Government 52

Monte Carlo

DECEMBER 8, 2023

While both data provenance vs. data lineage are mechanisms for understanding data at early stages, they differ in use cases. Data provenance is useful for validating and auditing data. Data lineage is useful for optimizing and troubleshooting data pipelines. Data lineage diagram.

Metadata 52

Metadata Data Data Warehouse Government 52

Snowflake

FEBRUARY 13, 2023

Snowflake kicked off 2023 with enhanced features around data governance and optimized storage for expanded data access. With over 250 clients in the Fortune 500 and Global 2000, apexanalytix is dedicated to providing companies and their suppliers with the ultimate supplier management experience.

Insurance 52

Insurance Banking Government Retail 52

AltexSoft

NOVEMBER 10, 2021

Well, there’s a new phenomenon in data management that received the name of a data lakehouse. The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. Data warehouse.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Monte Carlo

JULY 30, 2020

In the age of self-service business intelligence , nearly every company considers themselves a data-first company, but not every company is treating their data architecture with the level of democratization and scalability it deserves. Your company, for one, views data as a driver of innovation.

IT 45

IT Data Lake Business Intelligence Data Architecture 45

Monte Carlo

APRIL 1, 2021

As a result, data teams going the the lake or even lakehouse route often struggle to answer critical questions about their data such as: Where does my data live? How can I use this data? Is this data up-to-date? How is this data being used by the business? Data discovery tools and platforms can help.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Ascend.io

JULY 5, 2023

The data mesh framework helps organizations build shareable data sets securely, and at scale. Federated governance : This is the practice of decentralizing data governance to individual domains, while maintaining a set of overarching organizational rules and tools, facilitating both autonomy and coherence in data management.

Government 52

Government Data Data Pipeline Data Engineering 52

Edureka

FEBRUARY 9, 2023

Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions. Data ingestion, transformation, and storage are among their responsibilities, as are data governance and security. SQL is also an essential skill for Azure Data Engineers.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64

Knowledge Hut

SEPTEMBER 6, 2023

These certifications serve as concrete evidence of a professional's mastery, encompassing skills such as precise querying, data manipulation, database creation, and various data-related tasks. Data Management 3. Data Management 2. Data Management 2. Information System Core 2.

Database 52

Database Certification MongoDB MySQL 52

phData: Data Engineering

JULY 18, 2023

To truly understand its potential, we need to explore the benefits it brings, particularly when transitioning from traditional data management structures. Why Migrate to a Modern Data Stack? Improved Data Governance: This level of transparency can also enhance data governance and control mechanisms in the new data system.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

AltexSoft

AUGUST 29, 2023

If your organization fits into one of these categories and you’re considering implementing advanced data management and analytics solutions, keep reading to learn how data lakes work and how they can benefit your business. A data lakehouse may be an option if you want the best of both worlds. Data lake on AWS.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

ProjectPro

FEBRUARY 21, 2023

Due to the enormous amount of data being generated and used in recent years, there is a high demand for data professionals, such as data engineers, who can perform tasks such as data management, data analysis, data preparation, etc. The rest of the exam details are the same as the DP-900 exam.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Monte Carlo

APRIL 20, 2023

This way no decisions get made on bad data and our team becomes a proactive part of the solution,” said then Senior Director of Data at Freshly, Vitaly Lilich. Data access and enablement Data lineage is essential to data quality, but that is far from its only use case.

Data Warehouse 52

Data Warehouse BI Data Government 52

ProjectPro

JANUARY 31, 2022

Traditional data preparation platforms, including Apache Spark, are unnecessarily complex and inefficient, resulting in fragile and costly data pipelines. Several organizations can quickly transform, integrate, and analyze their data with Snowflake's Data Cloud.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52