Snowflake

NOVEMBER 2, 2023

And, since historically tools and commercial platforms were often designed to align with one specific architecture pattern, organizations struggled to adapt to changing business needs – which of course has implications on data architecture.

Data Lake 115

Data Lake Data Warehouse Cloud Unstructured Data 115

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Architecture 124

Architecture Metadata Kafka Government 124

Data Engineering Weekly

DECEMBER 16, 2024

Grab’s Metasense , Uber’s DataK9 , and Meta’s classification systems use AI to automatically categorize vast data sets, reducing manual efforts and improving accuracy. Beyond classification, organizations now use AI for automated metadata generation and data lineage tracking, creating more intelligent data infrastructures.

Data Engineering 62

Data Engineering Data Engineer Engineering Unstructured Data 62

AltexSoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Cloudera

NOVEMBER 17, 2022

While Cloudera CDH was already a success story at HBL, in 2022, HBL identified the need to move its customer data centre environment from Cloudera’s CDH to Cloudera Data Platform (CDP) Private Cloud to accommodate growing volumes of data. Smooth, hassle-free deployment in just six weeks.

Banking 85

Banking Management Data Lake Professional Services 85

Cloudera

MARCH 17, 2023

As the use of ChatGPT becomes more prevalent, I frequently encounter customers and data users citing ChatGPT’s responses in their discussions. I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics.

Education 64

Education Unstructured Data Data Lake Data Warehouse 64

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 high-level architecture shown below forms the backdrop for the exploration. Luke: Let’s talk about some of the fundamentals of modern data architecture.

Data Lake 83

Data Lake Analytics Application Cloud Storage Architecture 83

Monte Carlo

MAY 14, 2024

As organizations seek greater value from their data, data architectures are evolving to meet the demand — and table formats are no exception. But while the modern data stack , and how it’s structured, may be evolving, the need for reliable data is not — and that also has some real implications for your data platform.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Databand.ai

JULY 19, 2023

This capability is useful for businesses, as it provides a clear and comprehensive view of their data’s history and transformations. Data lineage tools are not a new concept. In this article: Why Are Data Lineage Tools Important? It provides context for data, making it easier to understand and manage.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

Monte Carlo

APRIL 1, 2021

Data Catalogs Can Drown in a Data Lake Although exceptionally flexible and scalable, data lakes lack the organization necessary to facilitate proper metadata management and data governance. Data discovery tools and platforms can help. Interested in learning how to scale data discovery across your data lake?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Government 52

Silectis

JANUARY 3, 2021

Big Data Large volumes of structured or unstructured data. Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Big Query Google’s cloud data warehouse.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Snowflake

JANUARY 26, 2023

requires multiple categories of data, from time series and transactional data to structured and unstructured data. initiatives, such as improving efficiency and reducing downtime by including broader data sets (both internal and external), offers businesses even greater value and precision in the results.

Data Ingestion 52

Data Ingestion Manufacturing Unstructured Data Architecture 52

Monte Carlo

JANUARY 23, 2023

But while most every company would consider themselves a “data-first” organization, not every data architecture is treated to the same level of democratization and scalability. In this post we’ll look at the dizzyingly buzzy data mesh and how it stacks up to the more traditional aggregated architectural approach of a data lake.

Data Lake 52

Data Lake Architecture Business Intelligence Unstructured Data 52

Snowflake

APRIL 5, 2023

With Snowflake’s support for multiple data models such as dimensional data modeling and Data Vault, as well as support for a variety of data types including semi-structured and unstructured data, organizations can accommodate a variety of sources to support their different business use cases.

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 52

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

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? Traditional data warehouse platform architecture. Metadata layer. Metadata layer.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

ProjectPro

SEPTEMBER 26, 2021

Becoming a Big Data Engineer - The Next Steps Big Data Engineer - The Market Demand An organization’s data science capabilities require data warehousing and mining, modeling, data infrastructure, and metadata management. Most of these are performed by Data Engineers.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Knowledge Hut

SEPTEMBER 29, 2023

The Azure Data Engineer Certification test evaluates one's capacity for organizing and putting into practice data processing, security, and storage, as well as their capacity for keeping track of and maximizing data processing and storage. They control and safeguard the flow of organized and unstructured data from many sources.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Monte Carlo

JUNE 14, 2023

Amazon S3 – An object storage service for structured and unstructured data, S3 gives you the compute resources to build a data lake from scratch. Data catalog Some organizations choose to implement data catalog solutions for data governance and compliance use cases. Now Go Build Some Data Pipelines!

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

JANUARY 31, 2023

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Knowledge Hut

NOVEMBER 28, 2023

With a plethora of new technology tools on the market, data engineers should update their skill set with continuous learning and data engineer certification programs. What do Data Engineers Do? Technical Data Engineer Skills 1.Python Knowing how to work with key-value pairs and object formats is still necessary.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Ascend.io

AUGUST 31, 2023

In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Central to this transformation are two shifts.

Data Lake 52

Data Lake Data Warehouse ETL Tools Data Pipeline 52

AltexSoft

MARCH 30, 2023

This way, Delta Lake brings warehouse features to cloud object storage — an architecture for handling large amounts of unstructured data in the cloud. Besides that, it’s fully compatible with various data ingestion and ETL tools. Databricks focuses on data engineering and data science.

Scala 64

Scala Data Lake Machine Learning BI 64

ProjectPro

OCTOBER 20, 2021

Data Integration at Scale Most data architectures rely on a single source of truth. Having multiple data integration routes helps optimize the operational as well as analytical use of data. A feature store is a modern, elegant solution to leverage data prep work from previous runs or other teams as well.

Machine Learning 52

Machine Learning Algorithm Data Science Government 52