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

Cloudera

OCTOBER 23, 2024

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI.

Metadata 83

Metadata BI Data Lake Business Intelligence 83

Monte Carlo

NOVEMBER 14, 2023

Databricks announced that Delta tables metadata will also be compatible with the Iceberg format, and Snowflake has also been moving aggressively to integrate with Iceberg. How Apache Iceberg tables structure metadata. Is your data lake a good fit for Iceberg? Limited data type support. Image courtesy of Dremio.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

Data Engineering Podcast

NOVEMBER 26, 2023

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Architecture 147

Architecture Data Lake High Quality Data SQL 147

Cloudera

OCTOBER 10, 2024

It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse. Table Cleanup: As tables grow, they often accumulate unused data files, manifest files, and snapshots that aren’t needed anymore.

IT 84

IT Data Lake Metadata Data Warehouse 84

Precisely

JUNE 24, 2024

The Precisely team recently had the privilege of hosting a luncheon at the Gartner Data & Analytics Summit in London. It was an engaging gathering of industry leaders from various sectors, who exchanged valuable insights into crucial aspects of data governance, strategy, and innovation.

Food 94

Food Data Analytics Pharmaceutical Consulting 94

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

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. How do we build data products ? How can we interoperate between the data domains ? Data As Code is a very strong choice : we do not want any UI because it is an heritage of the ETL period.

Technology 130

Technology Architecture Google Cloud Metadata 130

phData: Data Engineering

NOVEMBER 1, 2024

In an effort to better understand where data governance is heading, we spoke with top executives from IT, healthcare, and finance to hear their thoughts on the biggest trends, key challenges, and what insights they would recommend. Get the Trendbook What is the Impact of Data Governance on GenAI?

Government 52

Government Data Governance Finance Metadata 52

Precisely

JULY 18, 2024

Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata. As data grows exponentially, so do the complexities of managing and leveraging it to fuel AI and analytics.

Data Management 52

Data Management Management Metadata Database-centric 52

Monte Carlo

MAY 14, 2024

At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files. Table formats incorporate aspects like columns, rows, data types, and relationships, but can also include information about the structure of the data itself.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Snowflake

NOVEMBER 11, 2024

Implement better data governance by easily tracking and handling sensitive data The Lineage Visualization Interface (public preview) allows customers to easily track the flow of data and ML assets with an interactive interface in Snowsight.

Data Architecture 77

Data Architecture Architecture Data Lake Kafka 77

Precisely

JANUARY 25, 2024

There are three potential approaches to mainframe modernization: Data Replication creates a duplicate copy of mainframe data in a cloud data warehouse or data lake, enabling high-performance analytics virtually in real time, without negatively impacting mainframe performance. Best Practice 2. Best Practice 3.

Metadata 69

Metadata Relational Database Data Governance Government 69

Data Science Blog: Data Engineering

MAY 20, 2024

It offers full BI-Stack Automation, from source to data warehouse through to frontend. It supports a holistic data model, allowing for rapid prototyping of various models. It also supports a wide range of data warehouses, analytical databases, data lakes, frontends, and pipelines/ETL. pipelines, Azure Data Bricks.

Data Pipeline 52

Data Pipeline BI Data Lake Data Warehouse 52

Precisely

JUNE 6, 2023

The group kicked off the session by exchanging ideas about what it means to have a modern data architecture. Atif Salam noted that as recently as a year ago, the primary focus in many organizations was on ingesting data and building data lakes.

Data Architecture 52

Data Architecture Architecture Metadata Data Lake 52

Monte Carlo

MAY 18, 2023

Whether you’re a data scientist, data engineer, or business analyst, keeping track of your data’s origin, transformation, and movement is crucial for maintaining transparency, enforcing data governance, and ensuring data quality. The Spark data lake lineage example is helpful for context here.

Metadata 64

Metadata Data Lake Government Data Governance 64

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

Towards Data Science

JULY 24, 2023

Closely related to this is how those same platforms are bundling or unbundling related data services from data ingestion and transformation to data governance and monitoring. Why are these things related, and more importantly, why should data leaders care? Take data governance for example.

Metadata 95

Metadata Data Warehouse Data Lake Data Science 95

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

Monte Carlo

FEBRUARY 21, 2023

In this post, we’ll discuss what, exactly, a data fabric is, how other companies have used it, and how you can build one at your company. Table of Contents What is a data fabric? A data fabric infuses data governance and security across all forms of data, no matter its origin or destination within the organization.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

In this post, we’ll discuss what, exactly, a data fabric is, how other companies have used it, and how you can build one at your company. Table of Contents What is a data fabric? A data fabric infuses data governance and security across all forms of data, no matter its origin or destination within the organization.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Cloudera

JUNE 7, 2023

Agencies should inventory, categorize, and label data; protect data at rest and in transit; and deploy mechanisms to detect and stop data exfiltration. Agencies should carefully craft and review data governance policies to ensure all data lifecycle security aspects are appropriately enforced across the enterprise.”

Government 82

Government Metadata Data Lake Data 82

Silectis

FEBRUARY 3, 2021

Below we’ll cover the basics of data lineage, why it is important, and how Magpie enables teams to trust their data with this important new release. What is Data Lineage? Data lineage refers to the entire lifecycle of a dataset from its sources of origin all the way to its current state.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 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. In terms of infrastructure, what are the components of a modern data architecture and how has that changed over the years?

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

Databand.ai

JULY 28, 2022

In this very simplified example, we can see an ELT: Some pipeline tasks, probably running by Airflow , are scraping external data sources and collecting data from there. Those tasks are saving the extracted data in the data lake (or warehouse or lakehouse). This technique focuses directly on the data (vs.

Metadata 52

Metadata Data Lake Datasets Data Warehouse 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

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. Abstraction layer.

Process 69

Process Data Lake Metadata Data Warehouse 69

Databand.ai

AUGUST 30, 2023

Data silos: Legacy architectures often result in data being stored and processed in siloed environments, which can limit collaboration and hinder the ability to generate comprehensive insights. This requires implementing robust data integration tools and practices, such as data validation, data cleansing, and metadata management.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

The Modern Data Company

JANUARY 17, 2023

Leaders Can Easily Bring the CDP Under Federated Governance CDPs ingest data through both governed and ungoverned channels. These include internal data lakes, apps (1st or 3rd party), web SDK, internal or 3rd-party databases, and even spreadsheets generated within the marketing department.

Metadata 59

Metadata Government Data Lake Data 59

Snowflake

JUNE 4, 2024

This includes pipelines and transformations with Snowpark, Streams, Tasks and Dynamic Tables (public preview soon); extending AI and ML to Iceberg with Snowflake Cortex AI; performing storage maintenance with capabilities like automatic clustering and compaction; as well as securely collaborating on live data shares.

Government 84

Government Data Ingestion Data PostgreSQL 84

Cloudera

MARCH 23, 2022

The table information (such as schema, partition) is stored as part of the metadata (manifest) file separately, making it easier for applications to quickly integrate with the tables and the storage formats of their choice. Enterprise grade security and data governance – centralized data authorization to lineage and auditing.

Metadata 91

Metadata Data Architecture BI Machine Learning 91

Cloudera

SEPTEMBER 15, 2022

Mark: The first element in the process is the link between the source data and the entry point into the data platform. At Ramsey International (RI), we refer to that layer in the architecture as the foundation, but others call it a staging area, raw zone, or even a source data lake. See below. .

Data Lake 82

Data Lake Analytics Application Cloud Storage Architecture 82

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

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 Management 52

Ascend.io

JULY 19, 2023

But something about data mesh feels different, doesn’t it? For one, data mesh tackles the real headaches caused by an overburdened data lake and the annoying game of tag that’s too often played between the people who make data, the ones who use it, and everyone else caught in the middle.

Data Governance 40

Data Governance Government Metadata Data 40

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: workload analysis and replication, migrating or bursting to cloud, data warehouse optimization, and more. SECURITY AND GOVERNANCE LEADERSHIP. Enterprise Data Cloud: West Midlands Police — WMP public cloud data platform allows fast data insights and positive community interventions .

Food 69

Food Healthcare Government Medical 69

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