AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 104

Enterprise Data Warehouse Snapshot Cost-Benefit 104

Corinium

APRIL 25, 2019

Most of my days focus on understanding what’s happening in the market, defining overall product strategy and direction, and translating into execution across the various teams. Why should Chief Data & Analytics Officers care about data security? In data-driven organizations, data is flowing.

Insurance 150

Insurance Risk IoT Data-driven 150

AWS Big Data

JANUARY 8, 2024

In the subsequent post in our series, we will explore the architectural patterns in building streaming pipelines for real-time BI dashboards, contact center agent, ledger data, personalized real-time recommendation, log analytics, IoT data, Change Data Capture, and real-time marketing data.

Analytics 130

Analytics IoT Data-driven Snapshot 130

AWS Big Data

JULY 28, 2023

Tagging Consider tagging your Amazon Redshift resources to quickly identify which clusters and snapshots contain the PII data, the owners, the data retention policy, and so on. Redshift resources, such as namespaces, workgroups, snapshots, and clusters can be tagged. Tags provide metadata about resources at a glance.

Snapshot 96

Snapshot Metadata Measurement Data Warehouse 96

AWS Big Data

FEBRUARY 1, 2023

Every day, Amazon devices process and analyze billions of transactions from global shipping, inventory, capacity, supply, sales, marketing, producers, and customer service teams. This data is used in procuring devices’ inventory to meet Amazon customers’ demands. Then we chose Amazon Athena as our query service.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Cloudera

SEPTEMBER 12, 2022

A data lakehouse that enables multiple engines to run on the same data improves speed to market and productivity of users. . Cloudera has supported data lakehouses for over five years. Applying the Iceberg table format to all the organization’s data in the data lake makes it more performant and usable at scale.

Unstructured Data 75

Unstructured Data Data Architecture Data Lake Snapshot 75

Domino Data Lab

JANUARY 11, 2021

Data Science works best with a high degree of data granularity when the data offers the closest possible representation of what happened during actual events – as in financial transactions, medical consultations or marketing campaign results. About Domino Data Lab. Integration Features.

Recreation/Entertainment 103

Recreation/Entertainment Data Science Data Warehouse Publishing 103

AWS Big Data

MARCH 3, 2023

From detailed design to a beta release, Tricentis had customers expecting to consume data from a data lake specific to only their data, and all of the data that had been generated for over a decade. Data export As stated earlier, some customers want to get an export of their test data and create their data lake.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

MARCH 18, 2024

Namespaces group together all of the resources you use in Redshift Serverless, such as schemas, tables, users, datashares, and snapshots. First, we need to give our Redshift namespace permission via AWS Identity and Access Management (IAM) to access subscriptions on AWS Data Exchange. Workgroup – A collection of compute resources.

Data Warehouse 102

Data Warehouse Visualization Snapshot Data-driven 102

AWS Big Data

JULY 19, 2023

We show how to perform extract, transform, and load (ELT), an integration process focused on getting the raw data from a data lake into a staging layer to perform the modeling. The data (business process) needs to be integrated across various departments, in this case, marketing can access the sales data.

Modeling 84

Modeling Sales Data Warehouse Snapshot 84

AWS Big Data

MARCH 20, 2023

The two main approaches organizations employ to increase revenue are to expand geographically to enter new markets and to increase market share within a market by improving customer experience (CX). Improving CX is a well-known guideline to attract and retain customers and thereby increase the market share.

Analytics 52

Analytics Slice and Dice Data Processing Data Lake 52

AWS Big Data

JUNE 12, 2023

One notable trend in the streaming solutions market is the widespread use of Apache Kafka for data ingestion and Apache Spark for streaming processing across industries. Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed Apache Kafka service that offers a seamless way to ingest and process streaming data.

Management 93

Management Metadata Internet of Things Testing 93

AWS Big Data

DECEMBER 20, 2024

Jumia is present in NYSE and has a market cap of $554 million. In this post, we share part of the journey that Jumia took with AWS Professional Services to modernize its data platform that ran under a Hadoop distribution to AWS serverless based solutions. This process brings data from all the different layers of the data lake.

Metadata 117

Metadata Data-driven Snapshot Data Lake 117

AWS Big Data

FEBRUARY 18, 2025

To optimize their security operations, organizations are adopting modern approaches that combine real-time monitoring with scalable data analytics. They are using data lake architectures and Apache Iceberg to efficiently process large volumes of security data while minimizing operational overhead.

Snapshot 77

Snapshot Optimization Data Lake Metadata 77

AWS Big Data

NOVEMBER 6, 2024

Second, because traditional data warehousing approaches are unable to keep up with the volume, velocity, and variety of data, engineering teams are building data lakes and adopting open data formats such as Parquet and Apache Iceberg to store their data.

Metadata 114

Metadata Data Lake Management Internet of Things 114

Cloudera

DECEMBER 3, 2024

Constant data duplication, complex Extract, Transform & Load (ETL) pipelines, and sprawling infrastructure leads to prohibitively expensive solutions, adversely impacting the Time to Value, Time to Market, overall Total Cost of Ownership (TCO), and Return on Investment (ROI) for the business.

Metadata 84

Metadata Data Warehouse ROI Snapshot 84