AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74

Jet Global

NOVEMBER 7, 2023

The answer depends on your specific business needs and the nature of the data you are working with. Both methods have advantages and disadvantages: Replication involves periodically copying data from a source system to a data warehouse or reporting database. The alternative to BICC is BI Publisher (BIP)​.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data lakehouse was created to solve these problems.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

IBM Big Data Hub

JULY 5, 2022

Back in the 1960s and 70s, vast amounts of data were stored in the world’s new mainframe computers—many of them IBM System/360 machines—and had become a problem. Finally, 13 years after Codd published his paper, IBM Db2 on z/OS was born, and 10 years after that the first IBM Db2 database for LUW was released. . They were expensive.

Data Lake 88

Data Lake Data Warehouse Publishing Structured Data 88

AWS Big Data

FEBRUARY 21, 2023

Toucan natively integrates with Redshift Serverless, which enables you to deploy a scalable data stack in minutes without the need to manage any infrastructure component. Amazon Redshift is a fully managed cloud data warehouse service that enables you to analyze large amounts of structured and semi-structured data.

Visualization 52

Visualization Dashboards Data Warehouse Cost-Benefit 52

erwin

JUNE 26, 2020

Given the value this sort of data-driven insight can provide, the reason organizations need a data catalog should become clearer. It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., Business Metadata.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

Cloudera

OCTOBER 17, 2023

Kafka-centric approaches leave a lot to be desired, most notably operational complexity and difficulty integrating batch data, so there is certainly a gap to be filled. Lastly, real-time processing and movement of multi structured data including prompts and embeddings is critical for harnessing the transformative power of AI.

Data-driven 77

Data-driven Enterprise IoT Data Warehouse 77

Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. Yet metadata about the data contained in spreadsheets, including (but not limited to) the name, location, purpose, data source, and ownership does not often exist.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

Jet Global

MARCH 13, 2024

While Microsoft Dynamics is a powerful platform for managing business processes and data, Dynamics AX users and Dynamics 365 Finance & Supply Chain Management (D365 F&SCM) users are only too aware of how difficult it can be to blend data across multiple sources in the Dynamics environment.

Reporting 52

Reporting Finance Data Quality Sales 52

Sisense

JUNE 30, 2020

The data drawn from power visualizations comes from a variety of sources: Structured data , in the form of relational databases such as Excel, or unstructured data, deriving from text, video, audio, photos, the internet and smart devices. Her debut novel, The Book of Jeremiah , was published in 2019.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

AWS Big Data

AUGUST 16, 2023

Change Data Capture (CDC) in the context of a data lake refers to the process of capturing and propagating changes made to source data. Source systems often lack the capability to publish data that is modified or changed. About the authors Vijay Velpula is a Data Lake Architect with AWS Professional Services.

Data Lake 74

Data Lake Metadata Testing Snapshot 74

Jet Global

FEBRUARY 14, 2022

Structuring data in a way that recognizes the importance of tax from the outset is far more efficient than a silo approach and common data models will be key enablers of a more holistic process.”. In large organizations, this can require significant amounts of resource and (potentially) programming skills.

Finance 52

Finance Recreation/Entertainment Software Reporting 52

Cloudera

OCTOBER 3, 2018

Google built an innovative scale-out platform for data storage and analysis in the late 1990s and early 2000s, and published research papers about their work. In the data center and in the cloud, there’s a proliferation of players, often building on technology we’ve created or contributed to, battling for share.

Uncertainty 75

Uncertainty IoT Risk Reporting 75