AWS Big Data

MARCH 26, 2024

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Then, you transform this data into a concise format.

Data Strategy 72

Data Strategy Strategy Data Warehouse Prescriptive Analytics 72

Cloudera

JUNE 6, 2019

The typical Cloudera Enterprise Data Hub Cluster starts with a few dozen nodes in the customer’s datacenter hosting a variety of distributed services. Over time, workloads start processing more data, tenants start onboarding more workloads, and administrators (admins) start onboarding more tenants. Cloudera Manager (CM) 6.2

Metadata 85

Metadata Data Lake Optimization Strategy 85

Andrew White

JANUARY 9, 2022

On Thursday January 6th I hosted Gartner’s 2022 Leadership Vision for Data and Analytics webinar. Data mesh seems to mean a network of systems and hubs connected to help cope with silos. Perhaps a data mesh is what a pure architecture might design. Here is the link to the replay, in case you are interested.

Analytics 64

Analytics Measurement Modeling Data-driven 64

AWS Big Data

JULY 20, 2023

The system ingests data from various sources such as cloud resources, cloud activity logs, and API access logs, and processes billions of messages, resulting in terabytes of data daily. This data is sent to Apache Kafka, which is hosted on Amazon Managed Streaming for Apache Kafka (Amazon MSK).

Data Lake 90

Data Lake Analytics Snapshot Optimization 90

AWS Big Data

FEBRUARY 2, 2023

Since its launch in 2006, Amazon Simple Storage Service (Amazon S3) has experienced major growth, supporting multiple use cases such as hosting websites, creating data lakes, serving as object storage for consumer applications, storing logs, and archiving data. For Report path prefix , enter cur-data/account-cur-daily.

Reporting 90

Reporting Data Lake Management Optimization 90

Alation

JANUARY 17, 2023

What if, experts asked, you could load raw data into a warehouse, and then empower people to transform it for their own unique needs? Today, data integration platforms like Rivery do just that. By pushing the T to the last step in the process, such products have revolutionized how data is understood and analyzed.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

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. need to integrate multiple “point solutions” used in a data ecosystem) and organization reasons (e.g.,

Metadata 122

Metadata Cost-Benefit Enterprise Interactive 122

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. As a result, alternative data integration technologies (e.g.,

Data Processing 89

Data Processing Data Warehouse Enterprise Visualization 89

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

Jet Global

MAY 1, 2023

These licensing terms are critical: Perpetual license vs subscription: Subscription is a pay-as-you-go model that provides flexibility as you evaluate a vendor. Pricing model: The pricing scale is dependent on several factors. Some cloud applications can even provide new benchmarks based on customer data.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52