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

Data Engineering Podcast

MARCH 27, 2022

Summary Data governance is a practice that requires a high degree of flexibility and collaboration at the organizational and technical levels. The growing prominence of cloud and hybrid environments in data management adds additional stress to an already complex endeavor.

Data Governance 130

Data Governance Government Cloud Building 130

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.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Data Engineering Podcast

NOVEMBER 2, 2020

Summary Data lakes are gaining popularity due to their flexibility and reduced cost of storage. Along with the benefits there are some additional complexities to consider, including how to safely integrate new data sources or test out changes to existing pipelines.

Data Lake 100

Data Lake PostgreSQL Datasets Machine Learning 100

Data Engineering Podcast

JULY 22, 2019

Summary The current trend in data management is to centralize the responsibilities of storing and curating the organization’s information to a data engineering team. This organizational pattern is reinforced by the architectural pattern of data lakes as a solution for managing storage and access.

Data Lake 100

Data Lake Hadoop Data Architecture 100

phData: Data Engineering

APRIL 4, 2023

Fivetran today announced support for Amazon Simple Storage Service (Amazon S3) with Apache Iceberg data lake format. Amazon S3 is an object storage service from Amazon Web Services (AWS) that offers industry-leading scalability, data availability, security, and performance.

Data Lake 52

Data Lake Amazon Web Services Data Cleanse Data Warehouse 52

Grouparoo

JANUARY 11, 2022

This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle. There are two main options available, a data lake and a data warehouse. What is a Data Warehouse? What is a Data Lake?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

JANUARY 24, 2024

Data is among your company’s most valuable commodities, but only if you know how to manage it. More data, more access to data, and more regulations mean data governance has become a higher-stakes game. Data Governance Trends The biggest data governance trend isn’t really a trend at all—rather, it’s a state of mind.

Data Governance 52

Data Governance Government Data Lake Data Architecture 52

Monte Carlo

JUNE 2, 2021

As companies leverage more and more data to drive decision-making and maintain their competitive edge, it’s crucial that this data is accurate and reliable. Over the last few years, data lakes have emerged as a must-have for the modern data stack. What is data observability?

Data Lake 52

Data Lake Machine Learning Unstructured Data Datasets 52

Data Engineering Podcast

MAY 22, 2022

Acryl Data provides DataHub as an easy to consume SaaS product which has been adopted by several companies. Signup for the SaaS product at dataengineeringpodcast.com/acryl RudderStack helps you build a customer data platform on your warehouse or data lake. Stop struggling to speed up your data lake.

Machine Learning 130

Machine Learning Data Engineering Data Engineer Cloud 130

Data Engineering Podcast

FEBRUARY 19, 2023

Because of their complete ownership of your data they constrain the possibilities of what data you can store and how it can be used. Can you describe what Iceberg is and its position in the data lake/lakehouse ecosystem? Can you describe what Iceberg is and its position in the data lake/lakehouse ecosystem?

IT 147

IT Data Lake Metadata Data Warehouse 147

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 ? How do we govern all these data products and domains ? The number of subjects to automatize is not short.

Technology 130

Technology Architecture Google Cloud Metadata 130

Cloudera

JUNE 6, 2024

To keep pace as banking becomes increasingly digitized in Southeast Asia, OCBC was looking to utilize AI/ML to make more data-driven decisions to improve customer experience and mitigate risks. Lastly, data security is paramount, especially in the finance industry.

Banking 82

Banking Data Lake Finance Data Governance 82

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. This approach helps maintain accuracy, relevance, and compliance in generative AI applications.

Data Engineering 67

Data Engineering Data Engineer Pipeline-centric Engineering 67

Data Engineering Podcast

JUNE 2, 2024

Data governance is the binding force between these two parts of the organization. Nicola Askham found her way into data governance by accident, and stayed because of the benefit that she was able to provide by serving as a bridge between the technology and business. What are some of the pitfalls in data governance?

Data Governance 147

Data Governance Government Data Lake High Quality Data 147

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

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 Management Data Lake 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 Management Data Lake Data Warehouse 52

Christophe Blefari

JANUARY 20, 2024

You'll be seen as the most technical person of a data team and you'll need to help regarding "low-level" stuff you team. You'll be also asked to put in place a data infrastructure. It means a data warehouse, a data lake or other concepts starting with data. Is it really modern?

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Cloudera

MARCH 5, 2024

Struggling to access and collect, oftentimes disparate and siloed, data across environments that are required to power AI, many organizations are unable to achieve the business insight and value they had hoped for. Available for cloud and now also for the data center.

Data Lake 87

Data Lake Data Storage Government Kafka 87

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

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

Snowflake

JUNE 29, 2023

government agencies, including the DoD, can now use Snowflake for controlled unclassified information (CUI), including export controlled data, personally identifiable information (PII), and protected health information (PHI), among others. government-designated regions. Ready to learn more?

Education 52

Education Government Data Lake Data Security 52

The Modern Data Company

APRIL 15, 2024

Why Data Products Matter Imagine if managing your company’s data was as straightforward as using your favorite smartphone app. Data Products aim to make this a reality by simplifying how data is accessed, used, and governed across your organization.

Government 52

Government Metadata Data Data Lake 52

Data Engineering Podcast

JANUARY 28, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data.

Data Lake 147

Data Lake Building High Quality Data AWS 147

Cloudera

JUNE 7, 2023

The revised ZTMM is organized by five categories or pillars: identity, devices, networks, applications and workloads, and data, and four levels of maturity: traditional, initial, advanced, and optimal. It operates independently from compute and storage layers, offering integrated security and governance based on metadata.

Metadata 82

Metadata Government Data Lake Data 82

Christophe Blefari

MARCH 4, 2023

In a nutshell AI should be use as a tool to empower members and augment their success, while prioritising trust, privacy, security, and fairness, providing transparency in AI usage, and the right governance should be put in place to maintain accountability over AI algorithms. You bring your own compute. At least for me.

Machine Learning 130

Machine Learning AWS Data Data Lake 130

Cloudera

MARCH 17, 2023

The table format provides the necessary structure for the unstructured data that is missing in a data lake, using a schema or metadata definition, to bring it closer to a data warehouse. Some of the popular table formats are Apache Iceberg, Delta Lake, Hudi, and Hive ACID.

Education 64

Education Unstructured Data Data Lake Data Warehouse 64

Data Engineering Weekly

MAY 12, 2024

These tools have streamlined development processes, improved operational efficiency, and enabled data-driven decision-making across government agencies. Atlassian emphasizes how crucial it is for its data lake, utilized by over half of its employees, to support continuous growth and adaptability.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Snowflake

SEPTEMBER 14, 2023

More than 50% of data leaders recently surveyed by BCG said the complexity of their data architecture is a significant pain point in their enterprise. As a result,” says BCG, “many companies find themselves at a tipping point, at risk of drowning in a deluge of data, overburdened with complexity and costs.”

Data Architecture 95

Data Architecture Architecture Hadoop Data Warehouse 95

DataKitchen

NOVEMBER 4, 2021

Cloud computing has made it much easier to integrate data sets, but that’s only the beginning. Creating a data lake has become much easier, but that’s only ten percent of the job of delivering analytics to users. It often takes months to progress from a data lake to the final delivery of insights.

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Process Data Process Pharmaceutical Data Lake 98

Snowflake

JUNE 21, 2023

As a founding member of the Snowflake Security Field CTO team, I can tell you that customers invariably ask: Can we use Snowflake’s data superpowers to get to the bottom of our security and governance questions? These security dashboards take advantage of the fact that security and governance is primarily a data problem.

Government 52

Government Data Lake Java SQL 52

Cloudyard

AUGUST 22, 2023

. “ Accessibility to data in Amazon S3-compatible storage” This exciting addition enables you to create external stages for various cloud storage services and devices that are highly and seamlessly compliant with the Amazon S3 REST API standards. As per the Cloudflare “R2 is the ideal object storage platform to build data lakes.

Bytes 52

Bytes Data Lake Cloud Storage Cloud 52

Monte Carlo

MARCH 4, 2024

Made For The Lakehouse: Iceberg and Delta There was a point in time not too long ago that data lake vs. data warehouse was a heated and important debate. Most major data cloud providers support both use cases. Today, these concepts have largely merged into a lakehouse architecture.

Metadata 52

Metadata Data Lake Data Warehouse Data Engineering 52

Knowledge Hut

NOVEMBER 2, 2023

Azure Data Ingestion Pipeline Create an Azure Data Factory data ingestion pipeline to extract data from a source (e.g., Azure SQL Database, Azure Data Lake Storage). Data Aggregation Working with a sample of big data allows you to investigate real-time data processing, big data project design, and data flow.

Data Engineering 52

Data Engineering Data Engineer Coding Project 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.

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Metadata Data Lake Government Data Governance 64