DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM! Conclusion.

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

CDW Research Hub

JULY 18, 2022

While many organizations understand the business need for a data and analytics cloud platform , few can quickly modernize their legacy data warehouse due to a lack of skills, resources, and data literacy. Security Data Lake. Learn more about our Security Data Lake Solution.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

AWS Big Data

MARCH 7, 2024

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. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 111

Data Lake Analytics Dashboards Metrics 111

AWS Big Data

MARCH 25, 2024

For example, in a chatbot, data events could pertain to an inventory of flights and hotels or price changes that are constantly ingested to a streaming storage engine. Furthermore, data events are filtered, enriched, and transformed to a consumable format using a stream processor.

Data Lake 88

Data Lake Unstructured Data Management Modeling 88

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 78

Data Warehouse Sales Visualization Data Processing 78

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

Ontotext

APRIL 10, 2024

“Any enterprise CEO really ought to be able to ask a question that involves connecting data across the organization, be able to run a company effectively, and especially to be able to respond to unexpected events. Most organizations are missing this ability to connect all the data together.”

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

David Menninger's Analyst Perspectives

NOVEMBER 30, 2021

TIBCO is a large, independent cloud-computing and data analytics software company that offers integration, analytics, business intelligence and events processing software. It enables organizations to analyze streaming data in real time and provides the capability to automate analytics processes.

Analytics 160

Analytics Data Warehouse Business Intelligence Software 160

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 82

Enterprise Data Warehouse Snapshot Cost-Benefit 82

AWS Big Data

DECEMBER 13, 2023

A CDC-based approach captures the data changes and makes them available in data warehouses for further analytics in real-time. usually a data warehouse) needs to reflect those changes in near real-time. This post showcases how to use streaming ingestion to bring data to Amazon Redshift.

Data Warehouse 96

Data Warehouse Snapshot Data Processing Management 96

AWS Big Data

JANUARY 31, 2023

We have collected some of the key talks and solutions on data governance, data mesh, and modern data architecture published and presented in AWS re:Invent 2022, and a few data lake solutions built by customers and AWS Partners for easy reference.

Data Lake 80

Data Lake Data Governance Data Architecture Machine Learning 80

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 91

Data Lake Snapshot Big Data Data-driven 91

CIO Business Intelligence

SEPTEMBER 12, 2022

Data from that surfeit of applications was distributed in multiple repositories, mostly traditional databases. Fazal instructed his IT team to collect every bit of data and methodically determine its use later, rather than lose “precious” data in the rush to build a massive data warehouse. “We

Data Warehouse 116

Data Warehouse Predictive Analytics Data Lake IoT 116

AWS Big Data

JANUARY 24, 2024

AWS-powered data lakes, supported by the unmatched availability of Amazon Simple Storage Service (Amazon S3), can handle the scale, agility, and flexibility required to combine different data and analytics approaches. About the Authors Pathik Shah is a Sr. Analytics Architect on Amazon Athena.

Snapshot 98

Snapshot Data Lake Metadata Optimization 98

AWS Big Data

APRIL 3, 2023

Tens of thousands of customers run business-critical workloads on Amazon Redshift , AWS’s fast, petabyte-scale cloud data warehouse delivering the best price-performance. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 96

Data Warehouse Testing Data Lake Data-driven 96

CIO Business Intelligence

APRIL 12, 2023

Real-time AI brings together streaming data and machine learning algorithms to make fast and automated decisions; examples include recommendations, fraud detection, security monitoring, and chatbots. The underpinning architecture needs to include event-streaming technology, high-performing databases, and machine learning feature stores.

Machine Learning 145

Machine Learning Cost-Benefit Data-driven Strategy 145

AWS Big Data

JANUARY 8, 2024

It aims to provide a framework to create low-latency streaming applications on the AWS Cloud using Amazon Kinesis Data Streams and AWS purpose-built data analytics services. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 111

Analytics IoT Data-driven Snapshot 111

Cloudera

JUNE 2, 2022

What is less frequently mentioned is that during this same time we have also seen a rapid increase of cloud services where data needs to be delivered (data lakes, lakehouses, cloud warehouses, cloud streaming systems, cloud business processes, etc.).

Enterprise 98

Enterprise Data Lake Data Collection Data-driven 98

CIO Business Intelligence

JULY 13, 2022

What is less frequently mentioned is that during this same time we have also seen a rapid increase of cloud services where data needs to be delivered (data lakes, lakehouses, cloud warehouses, cloud streaming systems, cloud business processes, etc.).

Enterprise 88

Enterprise Data Lake Data Collection Data-driven 88

CIO Business Intelligence

SEPTEMBER 8, 2022

To access data in real time — and ensure that it provides actionable insights for all stakeholders — organizations should invest in the foundational components that enable more efficient, scalable, and secure data collection, processing, and analysis.

Cost-Benefit 122

Cost-Benefit Internet of Things Data-driven Data Lake 122

AWS Big Data

SEPTEMBER 13, 2023

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.

Data Lake 89

Data Lake Data Processing Metadata Snapshot 89

AWS Big Data

NOVEMBER 9, 2023

The aim was to bolster their analytical capabilities and improve data accessibility while ensuring a quick time to market and high data quality, all with low total cost of ownership (TCO) and no need for additional tools or licenses. This process has been scheduled to run daily, ensuring a consistent batch of fresh data for analysis.

Data Warehouse 102

Data Warehouse Testing Data Quality Reporting 102

CIO Business Intelligence

DECEMBER 1, 2022

Now halfway into its five-year digital transformation, PepsiCo has checked off many important boxes — including employee buy-in, Kanioura says, “because one way or another every associate in every plant, data center, data warehouse, and store are using a derivative of this transformation.” billion in revenue.

Digital Transformation 144

Digital Transformation IoT Data-driven KPI 144

Cloudera

SEPTEMBER 15, 2022

July brings summer vacations, holiday gatherings, and for the first time in two years, the return of the Massachusetts Institute of Technology (MIT) Chief Data Officer symposium as an in-person event. A key area of focus for the symposium this year was the design and deployment of modern data platforms. What is a data fabric?

Data Lake 78

Data Lake Data Architecture Data-driven Data Warehouse 78

Andrew White

DECEMBER 9, 2019

Scope could be: Data (i.e. Information (processed data). Records (files, or what you might all unstructured data). Events or transactions. Analytical stewardship is a missing link in analytics, BI and data science. Analytic (the analytics itself). Images (i.e. Anything else you can think of.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

IBM Big Data Hub

OCTOBER 16, 2023

Curated foundation models, such as those created by IBM or Microsoft, help enterprises scale and accelerate the use and impact of the most advanced AI capabilities using trusted data. In addition to natural language, models are trained on various modalities, such as code, time-series, tabular, geospatial and IT events data.

Risk 77

Risk Modeling Management Metadata 77

Cloudera

SEPTEMBER 2, 2020

Additionally, lines of business (LOBs) are able to gain access to a shared data lake that is secured and governed by the use of Cloudera Shared Data Experience (SDX). Build use case-driven data applications with easy-to-use, self-serve experiences, such as Data Warehouse and Machine Learning, on CDP Private Cloud.

Cost-Benefit 65

Cost-Benefit Data Warehouse Data Lake Machine Learning 65

Alation

FEBRUARY 13, 2020

It is about hurricanes and big events like the California wildfires, but it is also about complex things like satellite launches, for example, or big building projects. A lot of people in our audience are looking at implementing data lakes or are in the middle of big data lake initiatives.

Data-driven 52

Data-driven Data Lake Enterprise Analytics 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

IBM Big Data Hub

SEPTEMBER 19, 2023

Diagnostic analytics: Diagnostic analytics helps pinpoint the reason an event occurred. An electrical engineer can use prescriptive analytics to digitally design and test out various electrical systems to see expected energy output and predict the eventual lifespan of the system’s components.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

In(tegrate) the Clouds

JUNE 23, 2016

Large-volume data integration is available to Hadoop-based data lakes or cloud-based data warehouses. Integration has to support the continuum of data velocities starting from batch all the way to continuous streams. Integration is event-based rather than clock-driven.

Data Integration 49

Data Integration Data Lake Data Warehouse Data-driven 49

AWS Big Data

JUNE 6, 2023

Unless, of course, the rest of their data also resides in the Google Cloud. In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake.

Analytics 55

Analytics Data Lake Testing Optimization 55

Cloudera

AUGUST 26, 2020

But if an exchange is able to process data in real-time and detect an unnatural pattern on this stock being traded at extremely high volumes which is affecting the value or price, it can trigger a stop immediately, preventing further disruption or manipulation. That is something that a solution like Flink can do in the background.

Data Lake 80

Data Lake Data Warehouse Technology Marketing 80

AWS Big Data

MARCH 28, 2023

In a data warehouse, a dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

Data Lake 69

Data Lake Testing Snapshot Sales 69

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.

Recreation/Entertainment 103

Recreation/Entertainment Data Science Data Warehouse Modeling 103

AWS Big Data

MAY 25, 2023

Many organizations today are using AWS Glue to build ETL pipelines that bring data from disparate sources and store the data in repositories like a data lake, database, or data warehouse for further consumption. EventBridge picks up the event from AWS Glue and triggers an AWS Lambda function.

Reporting 68

Reporting Metrics Optimization Data Lake 68

AWS Big Data

APRIL 8, 2024

Solution overview To demonstrate this new capability, we use a sample customer scenario where the finance team wants to access data owned by the sales team for financial analysis and reporting. The sales team has a pipeline that creates a dataset containing valuable information about ticket sales, popular events, venues, and seasons.

Finance 76

Finance Sales Publishing Metadata 76