AWS Big Data

DECEMBER 15, 2023

Many companies identify and label PII through manual, time-consuming, and error-prone reviews of their databases, data warehouses and data lakes, thereby rendering their sensitive data unprotected and vulnerable to regulatory penalties and breach incidents. For our solution, we use Amazon Redshift to store the data.

Data Lake 115

Data Lake Data Warehouse Big Data Structured Data 115

erwin

JUNE 26, 2020

It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., legacy systems, data warehouses, flat files stored on individual desktops and laptops, and modern, cloud-based repositories.).

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

AWS Big Data

JUNE 26, 2024

New feature: Custom AWS service blueprints Previously, Amazon DataZone provided default blueprints that created AWS resources required for data lake, data warehouse, and machine learning use cases. You can build projects and subscribe to both unstructured and structured data assets within the Amazon DataZone portal.

Data Lake 102

Data Lake Data Warehouse Unstructured Data Data Governance 102

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

AWS Big Data

FEBRUARY 26, 2025

Amazon SageMaker Lakehouse provides an open data architecture that reduces data silos and unifies data across Amazon Simple Storage Service (Amazon S3) data lakes, Redshift data warehouses, and third-party and federated data sources. AWS Glue 5.0 Finally, AWS Glue 5.0

Analytics 59

Analytics Data Lake Metadata Data Warehouse 59

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 103

Data Lake Data Warehouse Data-driven B2B 103

IBM Big Data Hub

APRIL 25, 2023

To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Now, let’s chat about why data warehouse optimization is a key value of a data lakehouse strategy. To effectively use raw data, it often needs to be curated within a data warehouse.

Optimization 56

Optimization Strategy Data Warehouse Cost-Benefit 56

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 78

Analytics Data Warehouse Data Lake Metadata 78

AWS Big Data

MARCH 27, 2024

The solution uses AWS services such as AWS HealthLake , Amazon Redshift , Amazon Kinesis Data Streams , and AWS Lake Formation to build a 360 view of patients. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse. We use on-demand capacity mode.

Data Analytics 105

Data Analytics Analytics Data Warehouse Data Lake 105

AWS Big Data

AUGUST 15, 2024

In this post, we show how to capture the data quality metrics for data assets produced in Amazon Redshift. Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data.

Data Quality 106

Data Quality Visualization Metadata Key Performance Indicator 106

Alation

MAY 16, 2023

Data Storage The data storage component of a pipeline provides secure, scalable storage for the data. Various data storage methods are available, including data warehouses for structured data or data lakes for unstructured, semi-structured, and structured data.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

Alation

JULY 13, 2021

We have seen the COVID-19 pandemic accelerate the timetable of cloud data migration , as companies evolve from the traditional data warehouse to a data cloud, which can host a cloud computing environment. Accompanying this acceleration is the increasing complexity of data. Complex data management is on the rise.

Strategy 52

Strategy Data mining Structured Data Data Governance 52

IBM Big Data Hub

JULY 5, 2022

Nedbank builds a scalable data warehouse architecture . Endless data but your queries aren’t fast enough. Empower real-time decision making and perform heavy computational analysis with built-in ML, insanely fast ingest, and querying of data in motion and at rest. Data security & governance .

Data Lake 86

Data Lake Data Warehouse Publishing Structured Data 86

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud.

Data Strategy 78

Data Strategy Strategy Data Warehouse Prescriptive Analytics 78

Laminar Security

APRIL 18, 2023

That’s why I’m pleased that today Laminar has announced the addition of Google Cloud and Snowflake to our existing support for Amazon Web Services (AWS) and Microsoft Azure, making ours the first cloud-native data security platform to support all major CSPs and data warehouse environments.

Data Warehouse 52

Data Warehouse Risk Cost-Benefit Structured Data 52

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. The many data warehouse systems designed in the last 30 years present significant difficulties in that respect.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

AWS Big Data

OCTOBER 20, 2023

We’ve seen a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With these connectors, you can bring the data from Azure Blob Storage and Azure Data Lake Storage separately to Amazon S3.

Data Lake 96

Data Lake Big Data Data Warehouse Consulting 96

AWS Big Data

JULY 28, 2023

Organizations must comply with these requests provided that there are no legitimate grounds for retaining the personal data, such as legal obligations or contractual requirements. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud.

Snapshot 90

Snapshot Metadata Measurement Data Warehouse 90

Alation

MAY 16, 2023

Data Storage The data storage component of a pipeline provides secure, scalable storage for the data. Various data storage methods are available, including data warehouses for structured data or data lakes for unstructured, semi-structured, and structured data.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly.

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 52

Corinium

APRIL 25, 2019

It definitely depends on the type of data, no one method is always better than the other. For a large volume of structured data, for example, a customer master or data warehouse, where there are many stakeholders in your organization who need to see different subsets, tokenization is generally better.

Insurance 150

Insurance Risk IoT Data-driven 150

Alation

OCTOBER 21, 2021

But, on the back end, data lakes give businesses a common repository to collect and store data, streamlined usage from a single source, and access to the raw data necessary for today’s advanced analytics and artificial intelligence (AI) needs. Irrelevant data. Ungoverned data. Subscribe to Alation's Blog.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 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