DareData

JULY 5, 2023

Learn how we build data lake infrastructures and help organizations all around the world achieving their data goals. In today's data-driven world, organizations are faced with the challenge of managing and processing large volumes of data efficiently. And what is the reason for that?

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Monte Carlo

APRIL 1, 2021

Over the past few years, data lakes have emerged as a must-have for the modern data stack. But while the technologies powering our access and analysis of data have matured, the mechanics behind understanding this data in a distributed environment have lagged behind. Data discovery tools and platforms can help.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Monte Carlo

MAY 14, 2024

Depending on the quantity of data flowing through an organization’s pipeline — or the format the data typically takes — the right modern table format can help to make workflows more efficient, increase access, extend functionality, and even offer new opportunities to activate your unstructured data.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

Data Engineering Weekly

MARCH 3, 2024

The migration enhanced data quality, lineage visibility, performance improvements, cost reductions, and better reliability and scalability, setting a robust foundation for future expansions and onboarding. link] Martin Chesbrough: How to Build a Modern Data Team?

Data Engineering 67

Data Engineering Data Engineer Pipeline-centric Engineering 67

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

Towards Data Science

DECEMBER 4, 2023

A robust data infrastructure is a must-have to compete in the F1 business. We’ll build a data architecture to support our racing team starting from the three canonical layers : Data Lake, Data Warehouse, and Data Mart. Data Layers can be often combined together, sometimes in a single platform.

Data Engineering 84

Data Engineering Data Engineer Engineering Data Lake 84

Knowledge Hut

MARCH 28, 2024

Role Level Intermediate Responsibilities Design and develop data pipelines to ingest, process, and transform data. Implemented and managed data storage solutions using Azure services like Azure SQL Database , Azure Data Lake Storage, and Azure Cosmos DB. GDPR, HIPAA), and industry standards.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Monte Carlo

JANUARY 16, 2024

In this blog post, we’ll look at six innovations that are shaping the future of the data warehousing, as well as challenges and considerations that organizations should keep in mind. Data lake and data warehouse convergence 2. Easier to stream real-time data 3. Zero-copy data sharing 4.

Data Lake 52

Data Lake Data Warehouse Unstructured Data AWS 52

Snowflake

JUNE 27, 2023

Supporting mission criticality with enhanced native data governance, new Snowflake UIs, a growing compliance footprint, and updated cross-cloud business continuity At Snowflake, we’re committed to providing best-in-class native data governance features for customers entrusting our platform with their data.

Data Governance 57

Data Governance Unstructured Data Government SQL 57

Snowflake

JANUARY 22, 2024

Fidelity’s data scientists use the AI/ML-enabled Enterprise Analytics Platform to process a large volume of structured and unstructured data for deeper insights and better decision-making. In 2020, Fidelity kicked off its digital transformation and established an Enterprise Data Lake (EDL) along with Data Labs.

Engineering 63

Engineering Data Lake Unstructured Data Metadata 63

Cloudera

DECEMBER 11, 2020

The Data Security and Governance category, at the annual Data Impact Awards, has never been so important. The sudden rise in remote working, a huge influx in data as the world turned digital, not to mention the never-ending list of regulations businesses need to remain compliant with (how many acronyms can you name in full?

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

Monte Carlo

AUGUST 19, 2023

By integrating tools from a variety of vendors, a data platform enables a data engineering team to not only manage an organization’s data but also activate it for a domain’s use cases. In today’s data-driven landscape, building a data platform is no longer a nice-to-have, but a necessity for most organizations.

Building 52

Building BI Data Lake Data Governance 52

Monte Carlo

FEBRUARY 21, 2023

A data fabric isn’t a standalone technology—it’s a data management architecture that leverages an integrated data layer atop underlying data in order to empower business leaders with real-time analytics and data-driven insights. That’s a model worth looking at when it comes to data governance,” says Bob.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

A data fabric isn’t a standalone technology—it’s a data management architecture that leverages an integrated data layer atop underlying data in order to empower business leaders with real-time analytics and data-driven insights. That’s a model worth looking at when it comes to data governance,” says Bob.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Unstructured data represents up to 80-90 percent of the entire datasphere.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

DareData

JANUARY 30, 2023

As the field of data science and machine learning continues to evolve, it is increasingly evident that data engineering cannot be separated from it. Gone are the days when organizations could rely on models trained and stored in notebooks without any structure, governance, or testing. Introduction to Designing Data Lakes in AWS.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Precisely

MARCH 27, 2023

As part of the project, the company implemented a data governance program and rolled out scalable data quality tools to enhance the overall value it could deliver to its go-to-market organization. After several false starts, the company engaged Precisely Strategic Services to help align its people, processes, and technology.

Food 52

Food Consulting Pharmaceutical Data Lake 52

Databand.ai

JULY 19, 2023

Often, the extraction process includes checks and balances to verify the accuracy and completeness of the extracted data. The Load Phase After the data is extracted, it’s loaded into a data storage system in the load phase. The data is loaded as-is, without any transformation.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

Cloudera

SEPTEMBER 15, 2022

Mark: While most discussions of modern data platforms focus on comparing the key components, it is important to understand how they all fit together. The collection of source data shown on your left is composed of both structured and unstructured data from the organization’s internal and external sources.

Data Lake 81

Data Lake Analytics Application Cloud Storage Architecture 81

Cloudera

NOVEMBER 18, 2021

By adopting a custom developed application based on the Cloudera ecosystem, Carrefour has combined the legacy systems into one platform which provides access to customer data in a single data lake. Security & Governance Leadership.

Banking 76

Banking Data Lake Telecommunication Data 76

Monte Carlo

JUNE 14, 2023

The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses. Zero ETL is a bit of a misnomer.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

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., difficulty to achieve cross-organizational governance model).

Architecture 124

Architecture Metadata Government Kafka 124

AltexSoft

NOVEMBER 10, 2021

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. What is a data lakehouse? Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 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

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. This language is used to interact with databases and perform data manipulations and querying.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Monte Carlo

AUGUST 31, 2023

Data pipelines can handle both batch and streaming data, and at a high-level, the methods for measuring data quality for either type of asset are much the same. In many ways, the cloud makes data easier to manage, more accessible to a wider variety of users, and far faster to process.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

AltexSoft

AUGUST 22, 2022

A data fabric is an architecture design presented as an integration and orchestration layer built on top of multiple disjointed data sources like relational databases , data warehouses , data lakes, data marts , IoT , legacy systems, etc., to provide a unified view of all enterprise data.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

AltexSoft

NOVEMBER 23, 2021

If the transformation step comes after loading (for example, when data is consolidated in a data lake or a data lakehouse ), the process is known as ELT. You can learn more about how such data pipelines are built in our video about data engineering. Enhanced data security and governance.

Process 69

Process Data Lake Metadata Data Warehouse 69

phData: Data Engineering

JANUARY 3, 2022

This means it’s business-critical that companies can derive value from their data to better inform business decisions, protect their enterprise and their customers, and grow their business. This comprehensive guide will cover all of the basics of data engineering including common roles, functions, and responsibilities.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

Monte Carlo

MARCH 24, 2023

Data duplication When using multiple sources, or in the process of re-running failed jobs you might end up with the same data entered more than once. Data governance, compliance and access management Moving a table is relatively simple. Security can also be a challenge if the migration involves unstructured data.

Data Warehouse 52

Data Warehouse AWS Cloud Data Governance 52