Cloudera

JUNE 1, 2021

Said simply, Datacoral offers a fully-managed service for worry-free data integrations. Future-proof, “no-code” connectors enable customers to extract data from a wide range of popular data sources, and multi-level transformations are automatically orchestrated using, just, SQL. investor-relations@cloudera.com.

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

AWS Big Data

FEBRUARY 8, 2023

Vyaire developed a custom data integration platform, iDataHub, powered by AWS services such as AWS Glue , AWS Lambda , and Amazon API Gateway. In this post, we share how we extracted data from SAP ERP using AWS Glue and the SAP SDK. To learn more about AWS Glue, check out AWS Glue Documentation.

Testing 71

Testing Data Integration Data Lake Enterprise 71

erwin

JANUARY 11, 2019

A company can’t effectively implement data governance – documenting and applying business rules and processes, analyzing the impact of changes and conducting audits – if it fails at data management. The problem usually starts by relying on manual integration methods for data preparation and mapping.

Data Governance 40

Data Governance Risk Metadata Management 40

AWS Big Data

JULY 19, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning, and application development. This connector enables your data to be portable across Google Cloud Storage and Amazon S3.

Big Data 79

Big Data Software Consulting Unstructured Data 79

Jet Global

OCTOBER 7, 2020

There are five categories of data entities based on their functions and the type of data that they serve: Parameter (e.g., Document (e.g., When it comes to using data entities, you have two choices: out-of-the-box or custom data entities. General Ledger). Reference (e.g., Tax Codes). Master (e.g., Customers).

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

AWS Big Data

DECEMBER 13, 2023

Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. If you haven’t deployed one, then follow the steps here in the AWS Documentation.

Data Warehouse 95

Data Warehouse Snapshot Data Processing Management 95

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 78

Data Lake Data Warehouse Data-driven Optimization 78

Ontotext

MARCH 8, 2023

However, this information is typically stored in disparate locations, often hidden within departmental documents or applications. As such, most large financial organizations have moved their data to a data lake or a data warehouse to understand and manage financial risk in one place.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 93

Analytics Visualization Data Integration Cost-Benefit 93

CIO Business Intelligence

FEBRUARY 22, 2024

Ultimately, CIOs may increasingly be held accountable for the veracity of the reporting, the third-party assurance of the data, and ensuring their organizations’ compliant disclosures align with their corporate ESG goals.” That’s where the single source of truth comes into perspective and increases performance,” Karcher says.

Software 98

Software Reporting KPI Enterprise 98

AWS Big Data

JUNE 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

Data Quality 71

Data Quality Data Lake Data-driven Metrics 71

Domino Data Lab

APRIL 3, 2019

The longer answer is that in the context of machine learning use cases, strong assumptions about data integrity lead to brittle solutions overall. They sold off most of the company later, retaining some of its IP, and are known to have kept copies of internal documents. in lieu of simply landing in a data lake.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

IBM Big Data Hub

OCTOBER 12, 2023

To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture. This type of architecture combines the performance and usability of a data warehouse with the flexibility and scalability of a data lake.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

BI-Survey

AUGUST 21, 2020

The primary modernization approach is data warehouse/ETL automation, which helps promote broad usage of the data warehouse but can only partially improve efficiency in data management processes. However, an automation approach alone is of limited usefulness when data management processes are inefficient.

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

Sisense

JULY 22, 2020

The trend has been towards using cloud-based applications and tools for different functions, such as Salesforce for sales, Marketo for marketing automation, and large-scale data storage like AWS or data lakes such as Amazon S3 , Hadoop and Microsoft Azure. Sisense provides instant access to your cloud data warehouses.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

BI-Survey

NOVEMBER 23, 2021

The transactional data was stored in isolated data sets and initially served only one purpose, namely, to document the transaction that had taken place. Over time, enterprises realized that data is worth more. Thus, alternative data architecture concepts have emerged, such as the data lake and the data lakehouse.

Digital Transformation 52

Digital Transformation Data Warehouse Data Lake Data-driven 52

AWS Big Data

NOVEMBER 29, 2023

It enables data engineers, data scientists, and analytics engineers to define the business logic with SQL select statements and eliminates the need to write boilerplate data manipulation language (DML) and data definition language (DDL) expressions. 11:41:51 Registered adapter: glue=1.7.1

Data Lake 100

Data Lake Management Metrics Data Warehouse 100

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. Metadata Management: In legacy implementations, changes to Data Products (e.g., Introduction.

Metadata 126

Metadata Cost-Benefit Enterprise Interactive 126

erwin

JULY 17, 2019

It improves IT and business data literacy and knowledge, supporting enterprise data governance and business enablement. It helps solve the lack of visibility and control over “data at rest” in databases, data lakes and data warehouses and “data in motion” as it is integrated with and used by key applications.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52