Striim

FEBRUARY 19, 2024

Overview of Data Mesh Data Mesh is a decentralized architectural approach designed to address large-scale data management issues by promoting domain-oriented data ownership and self-serve data infrastructure. Data Fabric and Data Mesh have different focuses.

Data Integration 52

Data Integration Data Government Data Governance 52

Data Engineering Weekly

FEBRUARY 25, 2024

[link] PayPal: Leveraging Spark 3 and NVIDIA’s GPUs to Reduce Cloud Cost by up to 70% for Big Data Pipelines PayPal's integration of Apache Spark 3 and NVIDIA GPUs has led to up to 70% cost savings in cloud expenses for big data and AI applications, processing petabytes of data across hundreds of thousands of jobs.

Data Engineering 62

Data Engineering Data Engineer Engineering Kafka 62

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. Sample of a high-level data architecture blueprint for Azure BI programs.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Knowledge Hut

JANUARY 18, 2024

For instance, automating data cleaning and transformation can save time and reduce errors in the data processing stage. Together, automation and DataOps are transforming the way businesses approach data analytics, making it faster, more accurate, and more efficient.

Data Analytics 52

Data Analytics Healthcare Machine Learning Algorithm 52

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

The Modern Data Company

APRIL 15, 2024

By adopting this product mindset, we make the data process less mysterious and better align it with strategic business goals. It encourages frequent releases based on real-world feedback, transforming data from a static resource into a dynamic asset that drives business growth.

Building 52

Building Raw Data Food Data 52

Precisely

MARCH 14, 2023

We optimize these products for use cases and architectures that will remain business-critical for years to come. With this module, you’ll be able to: Leverage capabilities from across our data portfolio – meaning access to solutions you already know and rely on in a SaaS-based design infrastructure. Bigger, better results.

Data Integration 52

Data Integration High Quality Data BI Data 52

Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Striim

NOVEMBER 8, 2023

In addition, large datasets can span multiple regions, each having its own data laws, privacy restrictions, and governing institutions. As a result, implementing data governance in this centralized system can be burdensome.

Architecture 52

Architecture Generalist Government Datasets 52

Cloudera

MAY 28, 2024

It’s not enough for businesses to implement and maintain a data architecture. The unpredictability of market shifts and the evolving use of new technologies means businesses need more data they can trust than ever to stay agile and make the right decisions.

Data Architecture 84

Data Architecture Architecture Data Lake Data Warehouse 84

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

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

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. What is data governance? billion in 2020 to $5.28

Data Governance 52

Data Governance Government Healthcare Programming 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.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

JANUARY 31, 2022

Snowflake Data Marketplace gives users rapid access to various third-party data sources. Moreover, numerous sources offer unique third-party data that is instantly accessible when needed. Snowflake's machine learning partners transfer most of their automated feature engineering down into Snowflake's cloud data platform.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Cloudera

OCTOBER 19, 2023

While navigating so many simultaneous data-dependent transformations, they must balance the need to level up their data management practices—accelerating the rate at which they ingest, manage, prepare, and analyze data—with that of governing this data.

Telecommunication 79

Telecommunication Data Architecture Government Architecture 79

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. Change data capture (CDC). Simplify data management . 1: Multi-function analytics .

Metadata 94

Metadata Data Architecture BI Machine Learning 94

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

AltexSoft

MAY 12, 2023

Unstructured data refers to information that lacks a predefined format or organization. In contrast, big data refers to large volumes of structured and unstructured data that are challenging to process, store, and analyze using traditional data management tools. Hadoop, Apache Spark).

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

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 127

Architecture Metadata Government Kafka 127

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? First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 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