AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 99

Data Warehouse Data Lake Analytics Machine Learning 99

Sisense

OCTOBER 6, 2020

Traditional methods of gathering and organizing data can’t organize, filter, and analyze this kind of data effectively. What seem at first to be very random, disparate forms of qualitative data require the capacity of data warehouses , data lakes , and NoSQL databases to store and manage them.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

AWS Big Data

MARCH 27, 2024

This means you can seamlessly combine information such as clinical data stored in HealthLake with data stored in operational databases such as a patient relationship management system, together with data produced from wearable devices in near real-time. To get started with this feature, see Querying the AWS Glue Data Catalog.

Data Analytics 89

Data Analytics Analytics Data Warehouse Data Lake 89

Alation

JANUARY 26, 2023

Control access Ensure that access to data is granted only on a need-to-know basis. This means that different access policies are applied to different sets of data. Enable two-factor authentication Two-factor authentication adds an extra layer of security to your system. Adopt an approach of access segregation.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

AWS Big Data

FEBRUARY 22, 2023

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

CIO Business Intelligence

APRIL 4, 2023

AI working on top of a data lakehouse, can help to quickly correlate passenger and security data, enabling real-time threat analysis and advanced threat detection. In order to move AI forward, we need to first build and fortify the foundational layer: data architecture. Want to learn more?

Data Architecture 52

Data Architecture Data Lake Data Warehouse Cost-Benefit 52

IBM Big Data Hub

DECEMBER 7, 2023

Initially, they were designed for handling large volumes of multidimensional data, enabling businesses to perform complex analytical tasks, such as drill-down , roll-up and slice-and-dice. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.

OLAP 63

OLAP Slice and Dice Cost-Benefit Data Warehouse 63

IBM Big Data Hub

MAY 9, 2023

At IBM, we believe it is time to place the power of AI in the hands of all kinds of “AI builders” — from data scientists to developers to everyday users who have never written a single line of code. With watsonx.data , businesses can quickly connect to data, get trusted insights and reduce data warehouse costs.

Data Warehouse 109

Data Warehouse Cost-Benefit Machine Learning Modeling 109

CIO Business Intelligence

SEPTEMBER 21, 2022

However, as data enablement platform, LiveRamp, has noted, CIOs are well across these requirements, and are now increasingly in a position where they can start to focus on enablement for people like the CMO.

Risk 105

Risk Data Lake Marketing Interactive 105

Ontotext

AUGUST 4, 2023

Thanks to the metadata that the data fabric relies on, companies can also recognize different types of data, what is relevant, and what needs privacy controls; thereby, improving the intelligence of the whole information ecosystem. Data fabric does not replace data warehouses, data lakes, or data lakehouses.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

Alation

FEBRUARY 20, 2020

Enterprises are… turning to data catalogs to democratize access to data, enable tribal data knowledge to curate information, apply data policies, and activate all data for business value quickly.”. In a recent webinar,“ Ready for a Machine Learning Data Catalog?

Machine Learning 52

Machine Learning Metadata Reporting Data-driven 52

erwin

JULY 17, 2019

Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there. Constructing A Digital Transformation Strategy: Data Enablement. Many organizations prioritize data collection as part of their digital transformation strategy.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Andrew White

JANUARY 11, 2021

Data and Analytics Governance: Whats Broken, and What We Need To Do To Fix It. Link Data to Business Outcomes. Does Data warehouse as a software tool will play role in future of Data & Analytics strategy? Data lakes don’t offer this nor should they. E.g. Data Lakes in Azure – as SaaS.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52