AWS Big Data

FEBRUARY 16, 2024

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3).

Data Lake 102

Data Lake Data Warehouse Testing Business Objectives 102

AWS Big Data

FEBRUARY 16, 2023

Amazon Redshift is the most widely used data warehouse in the cloud, best suited for analyzing exabytes of data and running complex analytical queries. Amazon QuickSight is a fast business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data.

Data Warehouse 83

Data Warehouse Sales Visualization Data Processing 83

CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architects are frequently part of a data science team and tasked with leading data system projects.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

AWS Big Data

MARCH 7, 2024

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. We think of this concept as inside-out data movement.

Data Lake 118

Data Lake Analytics Dashboards Metrics 118

AWS Big Data

JUNE 6, 2023

It provides insights and metrics related to the performance and effectiveness of data quality processes. In this post, we highlight the seamless integration of Amazon Athena and Amazon QuickSight , which enables the visualization of operational metrics for AWS Glue Data Quality rule evaluation in an efficient and effective manner.

Data Quality 74

Data Quality Metrics Visualization Dashboards 74

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. AWS Glue provides both visual and code-based interfaces to make data integration effortless. The following diagram illustrates the solution architecture.

Analytics 100

Analytics IT Data Lake Visualization 100

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

Data Governance 100

Data Governance Unstructured Data Metadata Data Lake 100

AWS Big Data

OCTOBER 19, 2023

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure.

Data Lake 116

Data Lake Data Warehouse Visualization Snapshot 116

AWS Big Data

NOVEMBER 20, 2023

Use case A typical workload for AWS Glue for Apache Spark jobs is to load data from a relational database to a data lake with SQL-based transformations. The following is a visual representation of an example job where the number of workers is 10. Sean Ma is a Principal Product Manager on the AWS Glue team.

Metrics 100

Metrics Data Lake Cost-Benefit Dashboards 100

AWS Big Data

DECEMBER 5, 2023

This dynamic tool, powered by AWS and CARTO, provided robust visualizations of which regions and populations were interacting with our survey, enabling us to zoom in quickly and address gaps in coverage. Figure 1: Workflow illustrating data ingesting, transformation, and visualization using Redshift and CARTO.

Measurement 86

Measurement Dashboards Data Warehouse Analytics 86

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 88

Enterprise Data Warehouse Snapshot Cost-Benefit 88

AWS Big Data

MARCH 25, 2024

In this post, we discuss why data streaming is a crucial component of generative AI applications due to its real-time nature. In-context learning LLMs are trained with point-in-time data and have no inherent ability to access fresh data at inference time. For more information, refer to Dynamic Tables.

Data Lake 95

Data Lake Unstructured Data Management Modeling 95

AWS Big Data

MARCH 7, 2023

Decoupled and scalable – Serverless, auto scaled, and fully managed services are preferred over manually managed services. A data hub contains data at multiple levels of granularity and is often not integrated. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74

AWS Big Data

JUNE 28, 2023

However, to realize this growth, managing and preparing the data for analysis has to get easier. That’s why AWS is investing in a zero-ETL future so that builders can focus more on creating value from data, instead of preparing data for analysis. Firstly, it invariably requires data engineers to create custom code.

Analytics 71

Analytics Data Warehouse Data Lake Data-driven 71

Cloudera

OCTOBER 13, 2020

In the beginning, CDP ran only on AWS with a set of services that supported a handful of use cases and workload types: CDP Data Warehouse: a kubernetes-based service that allows business analysts to deploy data warehouses with secure, self-service access to enterprise data. That Was Then. This is Now.

Data Warehouse 91

Data Warehouse Machine Learning Visualization Data Lake 91

Data Science 101

NOVEMBER 7, 2019

Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Synapse allows one to use SQL to query petabytes of data, both relational and non-relational, with amazing speed. Azure Arc allows deployment and management of Azure services to any environment which can run Kubernetes.

Data Science 106

Data Science Machine Learning Data Lake IoT 106

DataKitchen

JANUARY 3, 2022

Business analysts must rapidly deliver value and simultaneously manage fragile and error-prone analytics production pipelines. Data tables from IT and other data sources require a large amount of repetitive, manual work to be used in analytics. IT-created infrastructure such as a data lake/warehouse).

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

AWS Big Data

JUNE 6, 2023

It supports both data quality at rest and data quality in AWS Glue extract, transform, and load (ETL) pipelines. Data quality at rest focuses on validating the data stored in data lakes, databases, or data warehouses. The extracted data is stored in Amazon S3, which serves as the data lake.

Data Quality 71

Data Quality Data Lake Visualization Data-driven 71

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning.

Data Quality 96

Data Quality Statistics Data Lake Visualization 96

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

Data Science 80

Data Science Data Analytics Prescriptive Analytics Analytics 80

Cloudera

DECEMBER 21, 2020

Company data exists in the data lake. Data Catalog profilers have been run on existing databases in the Data Lake. A Cloudera Data Warehouse virtual warehouse with Cloudera Data Visualisation enabled exists. A Cloudera Data Engineering service exists. The Data Steward .

Dashboards 97

Dashboards Visualization Data Warehouse Data Lake 97

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy. The best way to drive value is through use cases.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

BizAcuity

MAY 16, 2022

Now, businesses, regardless of the industry, are leveraging data and Business Intelligence to stay ahead of the competition. In brief, business intelligence is about how well you leverage, manage and analyze business data. Data mining. Data mining allows refining and analyzing of the data on a near-real time basis.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

Jen Stirrup

MAY 5, 2020

You can also use Azure Data Lake storage as well, which is optimized for high-performance analytics. It has native integration with other data sources, such as SQL Data Warehouse, Azure Cosmos, database storage, and even Azure Blob Storage as well. You can use Visual Studio, which is a home for many developers.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

AWS Big Data

JANUARY 8, 2024

For high availability and durability, Kinesis Data Streams achieves high durability by synchronously replicating the streamed data across three Availability Zones in an AWS Region and gives you the option to retain data for up to 365 days.

Analytics 117

Analytics IoT Data-driven Snapshot 117

BizAcuity

JULY 13, 2021

In many cases, source data is captured in various databases and the need for data consolidation arises and typically it takes around 6-9 months to complete, and with a high budget in terms of provisioning for servers, either in cloud or on-premise, licenses for data warehouse platform, reporting system, ETL tools, etc.

Optimization 52

Optimization Marketing Analytics Data Warehouse 52

Sisense

APRIL 26, 2020

Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Structured vs unstructured data. However, both types of data play an important role in data analysis.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

Jet Global

JANUARY 15, 2021

With the rollout of Microsoft’s Dynamics 365 Business Central (D365 BC) and Microsoft Dynamics 365 Finance & Supply Chain Management (D365 F&SCM) , the company has moved toward rationalizing its portfolio of business applications, removing redundancy, and shifting to a cloud-first approach for the future.

Cost-Benefit 72

Cost-Benefit Data Lake Reporting OLAP 72

Jet Global

OCTOBER 7, 2020

For organizations considering a move to Microsoft Dynamics 365 Finance & Supply Chain Management (D365 F&SCM), or for those in the early stages of an implementation project, defining a clear strategy for curating data is a key to developing a comprehensive approach to reporting and analytics. Enterprise Business Intelligence.

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

AWS Big Data

APRIL 20, 2023

Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse. Amazon Redshift integration for Apache Spark helps developers seamlessly build and run Apache Spark applications on Amazon Redshift data.

Data Lake 80

Data Lake Data Warehouse Sales Data-driven 80

Jedox

OCTOBER 22, 2020

In addition to using data to inform your future decisions, you can also use current data to make immediate decisions. Some of the technologies that make modern data analytics so much more powerful than they used t be include data management, data mining, predictive analytics, machine learning and artificial intelligence.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

Andrew White

OCTOBER 22, 2021

This time, since we were virtual I only managed to close out the week with the 1-1 summary. Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Data Management Infrastructure/Data Fabric 5. Data Integration tactics 4.

IT 52

IT Data Lake Strategy Data Science 52

Sisense

OCTOBER 6, 2020

As quantitative data is always numeric, it’s relatively straightforward to put it in order, manage it, analyze it, visualize it, and do calculations with it. Spreadsheet software like Excel, Google Sheets, or traditional database management systems all mainly deal with quantitative data.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Speed and self-service.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Smart Data Collective

DECEMBER 13, 2022

However, computerization in the digital age creates massive volumes of data, which has resulted in the formation of several industries, all of which rely on data and its ever-increasing relevance. Data analytics and visualization help with many such use cases. It is the time of big data. Understand Your Audience.

Visualization 135

Visualization Key Performance Indicator Sales Data Lake 135

AWS Big Data

APRIL 6, 2023

In this post, Morningstar’s Data Lake Team Leads discuss how they utilized tag-based access control in their data lake with AWS Lake Formation and enabled similar controls in Amazon Redshift. We realized we needed a data warehouse to cater to all of these consumer requirements, so we evaluated Amazon Redshift.

Data Warehouse 87

Data Warehouse Data Lake Management Data-driven 87

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52