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. workerUtilization showed 1.0 100%) based on the workload requirements.

Metrics 96

Metrics Data Lake Cost-Benefit Dashboards 96

AWS Big Data

DECEMBER 5, 2023

To fill in the gaps in existing data, HR&A creates digital equity surveys to build a more complete picture before developing digital equity plans. HR&A has used Amazon Redshift Serverless and CARTO to process survey findings more efficiently and create custom interactive dashboards to facilitate understanding of the results.

Measurement 84

Measurement Dashboards Data Warehouse Analytics 84

DataKitchen

JUNE 12, 2023

We had been talking about “Agile Analytic Operations,” “DevOps for Data Teams,” and “Lean Manufacturing For Data,” but the concept was hard to get across and communicate. I spent much time de-categorizing DataOps: we are not discussing ETL, Data Lake, or Data Science.

Testing 130

Testing Data Lake Dashboards Data Science 130

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 96

Data Governance Unstructured Data Metadata Data Lake 96

AWS Big Data

MARCH 2, 2023

Many organizations are building data lakes to store and analyze large volumes of structured, semi-structured, and unstructured data. In addition, many teams are moving towards a data mesh architecture, which requires them to expose their data sets as easily consumable data products.

Data Lake 77

Data Lake Testing Interactive Unstructured Data 77

Corinium

JUNE 6, 2019

Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service. Newer methods can work with large amounts of data and are able to unearth latent interactions.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Jen Stirrup

MAY 5, 2020

Azure allows you to protect your enterprise data assets, using Azure Active Directory and setting up your virtual network. Other technologies, such as Azure Data Factory, can help process large amounts of data around in the cloud. You can use Visual Studio, which is a home for many developers. Azure Data Lake Store.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

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 113

Data Lake Data Warehouse Visualization Snapshot 113

AWS Big Data

MARCH 25, 2024

AWS Glue can interact with streaming data services such as Kinesis Data Streams and Amazon MSK for processing and transforming CDC data. With Amazon Managed Service for Apache Flink Studio , you can build and run Apache Flink stream processing applications using standard SQL, Python, and Scala in an interactive notebook.

Data Lake 91

Data Lake Unstructured Data Management Modeling 91

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. DeeQu is optimized to run data quality rules in minimal passes that makes it efficient.

Data Quality 95

Data Quality Statistics Data Lake Visualization 95

AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

AWS Big Data

OCTOBER 9, 2023

Data lakes have been gaining popularity for storing vast amounts of data from diverse sources in a scalable and cost-effective way. As the number of data consumers grows, data lake administrators often need to implement fine-grained access controls for different user profiles.

Data Lake 121

Data Lake Testing Big Data Management 121

AWS Big Data

JUNE 28, 2023

In case the data sources change, data engineers have to manually make changes in their code and deploy it again. Furthermore, the time required to build or change pipelines makes the data unfit for near-real-time use cases such as detecting fraudulent transactions, placing online ads, and tracking passenger train schedules.

Analytics 70

Analytics Data Warehouse Data Lake Data-driven 70

Cloudera

DECEMBER 21, 2020

You will learn all the parts of Cloudera’s Data Platform that together will accelerate your everyday Data Worker tasks. This demo-guided blog aims to inspire further curiosity and learning, as well as fuel a fruitful, interactive dialogue – we welcome you to reach out to us if any particular part piques your interest. .

Dashboards 98

Dashboards Visualization Data Warehouse Data Lake 98

AWS Big Data

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data. Jupyter notebooks are web-based interactive platforms.

Insurance 81

Insurance Visualization Data Lake Metrics 81

Cloudera

JANUARY 15, 2021

Impala has a longstanding reputation for high performance and concurrency, low latency for interactive queries, and the CPU efficiency of it’s C++ backend with dynamic code generation based on LLVM. As part of the broader CDP, CDW participates in a centralized security and governance model managed by CDP’s Shared Data Experience (SDX).

Data Warehouse 99

Data Warehouse Cost-Benefit Consulting Interactive 99

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. Create a visual.

Data Warehouse 81

Data Warehouse Sales Visualization Data Processing 81

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 85

Enterprise Data Warehouse Snapshot Cost-Benefit 85

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

Cloudera

JULY 18, 2018

For those asking big questions, in the case of healthcare, an incredible amount of insight remains hidden away in troves of clinical notes, EHR data, medical images, and omics data. To arrive at quality data, organizations are spending significant levels of effort on data integration, visualization, and deployment activities.

Machine Learning 52

Machine Learning Predictive Analytics Analytics Prescriptive Analytics 52

AWS Big Data

APRIL 20, 2023

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML).

Data Lake 78

Data Lake Data Warehouse Sales Data-driven 78

CIO Business Intelligence

JANUARY 19, 2023

Our data management is a key focus, including building data lakes and visual analytics capabilities that we are introducing across our entire enterprise. And this speed only becomes possible when all of those interactions are properly protected. We also have to make sure we have a secure platform.

Sales 52

Sales Data Lake Technology Data-driven 52

Sisense

JUNE 30, 2020

In a world increasingly dominated by data, users of all kinds are gathering, managing, visualizing, and analyzing data in a wide variety of ways. One of the downsides of the role that data now plays in the modern business world is that users can be overloaded with jargon and tech-speak, which can be overwhelming.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Sisense

JUNE 12, 2019

Last year, Sisense released both Sisense Narratives , which creates descriptive text to help end users understand their visualizations as well as Sisense Insight Miner , which looks for unusual relationships in the data and surfaces them for further analysis. Why AI Now? Building a Better Tomorrow.

Analytics 75

Analytics Data-driven Dashboards IoT 75

Alation

FEBRUARY 20, 2020

The result, as many industry observers have put it, is that many data lakes become data swamps. New data visualization user interfaces from Tableau and Qlik proved that any business user can analyze their own data. Get the latest data cataloging news and trends in your inbox.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

AWS Big Data

MAY 29, 2024

These users interact with and run analytical queries across AWS analytics services. To enable them to use the AWS services, their identities from the external IdP are mapped to AWS Identity and Access Management (IAM) roles within AWS, and access policies are applied to these IAM roles by data administrators.

Data Lake 81

Data Lake Enterprise Management Business Intelligence 81

Rita Sallam

AUGUST 17, 2016

A BeyondCore business person or citizen data scientist would ingest data into the platform and define an outcome variable. The user explores data via visualizations and natural language generated narration. Why BeyondCore is Disruptive.

Scorecard 40

Scorecard Visualization Sales Marketing 40

CIO Business Intelligence

JUNE 29, 2022

Azure Data Explorer is used to store and query data in services such as Microsoft Purview, Microsoft Defender for Endpoint, Microsoft Sentinel, and Log Analytics in Azure Monitor. Azure Data Lake Analytics. Data warehouses are designed for questions you already know you want to ask about your data, again and again.

Data Lake 113

Data Lake Analytics Data Warehouse Machine Learning 113

AWS Big Data

MARCH 1, 2023

Finding similar columns in a data lake has important applications in data cleaning and annotation, schema matching, data discovery, and analytics across multiple data sources. Finally, to interact with and visualize results from our solution, we build an interactive Streamlit web application running on AWS Fargate.

Data Lake 86

Data Lake Deep Learning Modeling Interactive 86

AWS Big Data

FEBRUARY 13, 2024

AWS Glue has made this more straightforward with the launch of AWS Glue job observability metrics , which provide valuable insights into your data integration pipelines built on AWS Glue. With Grafana, you can create, explore, and share visually rich, data-driven dashboards. Graph lines are visualized per job.

Metrics 99

Metrics Dashboards Visualization Key Performance Indicator 99

AWS Big Data

AUGUST 2, 2023

In this blog, we will walk through how we can apply existing enterprise data to better understand and estimate Scope 1 carbon footprint using Amazon Simple Storage Service (S3) and Amazon Athena , a serverless interactive analytics service that makes it easy to analyze data using standard SQL. usage_therms", "gasutilization"."usage_scf"

Data Lake 73

Data Lake Measurement Visualization Data Architecture 73

CIO Business Intelligence

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. Lakehouses redeem the failures of some data lakes.

Data Lake 139

Data Lake Data Warehouse Unstructured Data Business Intelligence 139

AWS Big Data

MAY 16, 2024

However, visualizing and analyzing large-scale geospatial data presents a formidable challenge due to the sheer volume and intricacy of information. This often overwhelms traditional visualization tools and methods. Figure 1 – Map built with CARTO Builder and the native support to visualize H3 indexes What are spatial indexes?

Data Warehouse 108

Data Warehouse Visualization Cost-Benefit Optimization 108

AWS Big Data

FEBRUARY 1, 2023

With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Ontotext

MARCH 8, 2023

Graphs reconcile such data continuously crawled from diverse sources to support interactive queries and provide a graphic representation or model of the elements within supply chain, aiding in pathfinding and the ability to semantically enrich complex machine learning (ML) algorithms and decision making.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

MARCH 17, 2023

Development teams had to provide a raw data file to internal users, upon request, to show the value of the new feature, and even then it was limited in how they could show value. Data visualization helps business analysts scale client support The sheer volume of our datasets made gathering insights a slow process.

Dashboards 52

Dashboards IT Data Lake Visualization 52

AWS Big Data

MARCH 26, 2024

Customer 360 (C360) provides a complete and unified view of a customer’s interactions and behavior across all touchpoints and channels. This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. Then, you transform this data into a concise format.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69