Ascend.io

APRIL 12, 2023

So when we talk about making data usable, we’re having a conversation about data integrity. Data integrity is the overall readiness to make confident business decisions with trustworthy data, repeatedly and consistently. Data integrity is vital to every company’s survival and growth.

Data Pipeline 52

Data Pipeline Data Integration Datasets Data 52

RandomTrees

APRIL 18, 2024

In today’s dynamic business landscape, data integration has become a critical component for enterprises to derive meaningful insights and make informed decisions. Among the various tools available for data integration, Informatica and Talend stand out as popular choices, each with its strengths and capabilities.

Coding 52

Coding Metadata Retail Python 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Metadata layer 4.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Metadata layer 4.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 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

Data Engineering Podcast

NOVEMBER 20, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. The biggest challenge with modern data systems is understanding what data you have, where it is located, and who is using it.

Systems 130

Systems Metadata Data Pipeline MongoDB 130

RandomTrees

FEBRUARY 6, 2024

Necessity for automation : Gen AI has the capacity to automate multiple data engineering processes, such as data integration, transformation, and pipeline creation, enabling data engineers to allocate their time to more valuable endeavors.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Data Engineering Podcast

DECEMBER 25, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan's active metadata capabilities. Missing data? Again, be prepared to have metadata challenges especially. Struggling with broken pipelines? Stale dashboards?

Building 100

Building Metadata Business Intelligence Data Lake 100

Data Engineering Weekly

DECEMBER 29, 2022

Data catalogs are the most expensive data integration systems you never intended to build. Data Catalog as a passive web portal to display metadata requires significant rethinking to adopt modern data workflow, not just adding “modern” in its prefix. The modern(?) What does that mean?

Metadata 62

Metadata Data Warehouse ETL Tools Data Workflow 62

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 67

Metadata Data Governance Relational Database Government 67

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

AWS 98

AWS Scala Metadata Data Lake 98

Snowflake

APRIL 5, 2023

Two different data modeling approaches—dimensional data modeling and Data Vault—each have their own pros and cons. Modernizing a data warehouse with Snowflake Data Cloud is a smart investment that can provide significant benefits to businesses of all sizes, today more than ever as data models become ever more complex.

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 52

Workfall

JUNE 12, 2023

It ensures that organisations stay at the forefront by capturing every twist and turn in the data landscape. With CDC by their side, organisations unlock the power of informed decision-making, safeguard data integrity, and enable lightning-fast analytics. CDC also plays a crucial role in data integration and ETL processes.

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

phData: Data Engineering

SEPTEMBER 19, 2023

Data modeling methodologies are systematic approaches used to design and define the structure and relationships of data within a system. They provide a framework for organizing and representing data elements, attributes, and relationships. Want to learn more about data governance?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Precisely

OCTOBER 16, 2023

The cloud is especially well-suited to large-scale storage and big data analytics, due in part to its capacity to handle intensive computing requirements at scale. BI platforms and data warehouses have been replaced by modern data lakes and cloud analytics solutions. Data integrity is also essential.

Cloud 70

Cloud Cloud Computing Metadata Data Governance 70

Towards Data Science

NOVEMBER 4, 2023

Often it is a data warehouse solution (DWH) in the central part of our infrastructure. Data warehouse exmaple. Introduction to Apache Iceberg Tables Simplified data integrations Managed solutions like Fivetran and Stitch were built to manage third-party API integrations with ease.

Data Engineering 83

Data Engineering Data Engineer Engineering BI 83

Data Engineering Podcast

MARCH 22, 2021

Datafold also helps automate regression testing of ETL code with its Data Diff feature that instantly shows how a change in ETL or BI code affects the produced data, both on a statistical level and down to individual rows and values. RudderStack’s smart customer data pipeline is warehouse-first.

Data Warehouse 100

Data Warehouse Metadata Data Lake Hadoop 100

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

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. It is designed to be easily queryable with SQL even for large analytic tables (we’re talking petabytes of data). How Apache Iceberg tables structure metadata.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

ProjectPro

FEBRUARY 16, 2023

Data Engineers and Data Scientists require efficient methods for managing large databases, which is why centralized data warehouses are in high demand. Cloud computing has made it easier for businesses to move their data to the cloud for better scalability, performance, solid integrations, and affordable pricing.

AWS 52

AWS Data Management ETL Tools Management 52

AltexSoft

NOVEMBER 23, 2021

Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization. To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization.

Process 69

Process Data Lake Metadata Data Warehouse 69

Monte Carlo

DECEMBER 8, 2023

Enter: data provenance and data lineage. Data lineage is a visual tool that tracks the movement and transformations of data through various systems, processes, and applications. Data provenance is the record of metadata from data’s original sources, providing the historical context and authenticity of data.

Metadata 52

Metadata Data Data Warehouse Government 52

Monte Carlo

DECEMBER 8, 2023

Enter: data provenance and data lineage. Data lineage is a visual tool that tracks the movement and transformations of data through various systems, processes, and applications. Data provenance is the record of metadata from data’s original sources, providing the historical context and authenticity of data.

Metadata 52

Metadata Data Data Warehouse Government 52

Towards Data Science

FEBRUARY 6, 2024

Order snapshots are stored in my own development area (image by the author) To prevent my extractions from impacting performance on the operational side, I queried this data regularly and stored it in a persistent staging area (PSA) within my data warehouse. Metadata update Data products need to be understandable.

Systems 80

Systems Raw Data Metadata Data Cleanse 80

Ascend.io

FEBRUARY 28, 2024

This process reduces noise in the data, which is crucial for the effectiveness of AI algorithms, especially in complex predictive models and deep learning applications. Such comprehensive metadata management is crucial in adhering to privacy and compliance standards, safeguarding AI operations against potential legal and ethical pitfalls.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Maxime Beauchemin

JANUARY 20, 2017

Data modeling is changing Typical data modeling techniques — like the star schema  — which defined our approach to data modeling for the analytics workloads typically associated with data warehouses, are less relevant than they once were.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

Grouparoo

FEBRUARY 9, 2022

The testing process is often performed during the initial setup of a data warehouse after new data sources are added to a pipeline and after data integration and migration projects. ETL testing can be challenging since most ETL systems process large volumes of heterogeneous data. Metadata testing.

Process 52

Process ETL System Data Warehouse Metadata 52

Monte Carlo

FEBRUARY 9, 2023

Over the past several years, data warehouses have evolved dramatically, but that doesn’t mean the fundamentals underpinning sound data architecture needs to be thrown out the window. What is a Data Vault model? Pie Insurance , a leading small business insurtech, leverages a data vault 2.0

Architecture 52

Architecture Raw Data Metadata Data Warehouse 52

Databand.ai

AUGUST 30, 2023

By using DataOps tools, organizations can break down silos, reduce time-to-insight, and improve the overall quality of their data analytics processes. DataOps tools can be categorized into several types, including data integration tools, data quality tools, data catalog tools, data orchestration tools, and data monitoring tools.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 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? Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Databand.ai

JULY 28, 2022

For instance, data lineage can help train (or re-train) data science models based on new data patterns. Data lineage not only delivers this visibility, but it can also reduce manual processes associated with teams tracking down this information or working through data silos.

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

Data Engineering Podcast

JANUARY 15, 2022

You can observe your pipelines with built in metadata search and column level lineage. StreamSets DataOps Platform is the world’s first single platform for building smart data pipelines across hybrid and multi-cloud architectures. You can observe your pipelines with built in metadata search and column level lineage.

Engineering 100

Engineering Electronics ETL Tools Data Pipeline 100

Towards Data Science

MARCH 5, 2024

At its core, BigQuery is a serverless Data Warehouse for analytical purposes and built-in features like Machine Learning ( BigQuery ML ). Traditionally, normalization has been hailed as a best practice, emphasizing the reduction of redundancy and the preservation of data integrity.

Bytes 70

Bytes Google Cloud Cloud Storage Utilities 70

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Knowledge Hut

JULY 24, 2023

But why do we need data integrity in a DBMS? In addition to data entered by users, database systems typically store large amounts of data. The system stores metadata about data which makes it easier to find and retrieve data. Data independence is of paramount importance in database management.

Database Design 52

Database Design Relational Database Metadata Database 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