DataKitchen

AUGUST 27, 2021

Marketing invests heavily in multi-level campaigns, primarily driven by data analytics. This analytics function is so crucial to product success that the data team often reports directly into sales and marketing. As figure 2 summarizes, the data team ingests data from hundreds of internal and third-party sources.

Analytics 246

Analytics Sales Testing Cost-Benefit 246

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. OpenSearch Service is used for multiple purposes, such as observability, search analytics, consolidation, cost savings, compliance, and integration.

Analytics 95

Analytics IT Data Lake Visualization 95

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

AWS Big Data

DECEMBER 5, 2023

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. This cut down significantly on analytical turnaround times.

Measurement 81

Measurement Dashboards Data Warehouse Analytics 81

Smart Data Collective

OCTOBER 27, 2021

An interactive analytics application gives users the ability to run complex queries across complex data landscapes in real-time: thus, the basis of its appeal. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights. Why Use an Interactive Analytics Application?

Interactive 111

Interactive Unstructured Data Analytics Data Warehouse 111

AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

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

DataKitchen

NOVEMBER 4, 2021

The requirement to integrate enormous quantities and varieties of data coupled with extreme pressure on analytics cycle time has driven the pharmaceutical industry to lead in DataOps adoption. The bottom line is how to attain analytic agility? It often takes months to progress from a data lake to the final delivery of insights.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

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 68

Analytics Data Warehouse Data Lake Data-driven 68

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

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

AWS Big Data

MARCH 29, 2024

Grafana provides powerful customizable dashboards to view pipeline health. QuickSight makes it straightforward for business users to visualize data in interactive dashboards and reports. Sample AWS CDK template This post provides a sample AWS CDK template for a dashboard using AWS Glue observability metrics.

Metrics 103

Metrics Visualization Dashboards Interactive 103

Andrew White

DECEMBER 9, 2019

This was a great inquiry since it called into question the perceived wisdom peddled by some that cataloging everything was a prerequisite for data (and analytics) governance. Modern data (and analytics) governance does not necessarily need: Wall-to-wall discovery of your data and metadata. The use case, and.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

AWS Big Data

NOVEMBER 20, 2023

For any modern data-driven company, having smooth data integration pipelines is crucial. These pipelines pull data from various sources, transform it, and load it into destination systems for analytics and reporting. When running properly, it provides timely and trustworthy information.

Metrics 93

Metrics Data Lake Cost-Benefit Dashboards 93

AWS Big Data

JUNE 6, 2023

As most organizations, that have turned to Google Analytics (GA) as a digital analytics solution, mature they discover a more pressing need to integrate this data silo with the rest of their organization’s data to enable better analytics and resulting product development and fraud detection.

Analytics 55

Analytics Data Lake Testing Optimization 55

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

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021. Third-party APIs – These provide analytics and survey data related to ecommerce websites.

Data Warehouse 103

Data Warehouse Testing Data Quality Reporting 103

Jedox

OCTOBER 22, 2020

The term “data analytics” refers to the process of examining datasets to draw conclusions about the information they contain. Data analysis techniques enhance the ability to take raw data and uncover patterns to extract valuable insights from it. Data analytics is not new. Self-service reporting.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

AWS Big Data

MARCH 25, 2024

To understand the best ways to make API calls via Apache Flink, refer to Common streaming data enrichment patterns in Amazon Kinesis Data Analytics for Apache Flink. OpenSearch Service provides support for native ingestion from Kinesis data streams or MSK topics.

Data Lake 88

Data Lake Unstructured Data Management Modeling 88

CIO Business Intelligence

APRIL 26, 2022

Backcountry also lacked many core services critical for an online retailer — no CMS, no analytics, no data platform, and no data lake. In recent years, e-commerce platforms have evolved into a combination of cloud, analytics, CX UIs, and data lakes dubbed customer data platforms (CDPs).

Data Lake 97

Data Lake Dashboards Recreation/Entertainment Sales 97

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. Of course some architectures featured both paradigms as well. In Closing.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

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 Engineer.

Dashboards 97

Dashboards Visualization Data Warehouse Data Lake 97

IBM Big Data Hub

OCTOBER 16, 2023

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

Risk 75

Risk Modeling Management Metadata 75

AWS Big Data

JUNE 6, 2023

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. The crawler builds a Data Catalog, so the data can be queried using Athena. Choose Visualize.

Data Quality 70

Data Quality Metrics Visualization Dashboards 70

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. What Are Data Entities?

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

BizAcuity

MAY 16, 2022

When data is stored in silos and the back-end systems are not able to process the massive amounts of data seamlessly, critical information may be lost. We get critical business insights based on how well we leverage our business data. Data mining. Visual Analytics and Data Visualization.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

CIO Business Intelligence

APRIL 12, 2023

He had been trying to gather new data insights but was frustrated at how long it was taking. Most current data architectures were designed for batch processing with analytics and machine learning models running on data warehouses and data lakes. A unified data ecosystem enables this in real time.

Machine Learning 133

Machine Learning Cost-Benefit Data-driven Strategy 133

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 76

Data Lake Data Warehouse Sales Data-driven 76

AWS Big Data

APRIL 19, 2023

With the right analytics approach, this is possible. In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

Jet Global

OCTOBER 30, 2020

Introducing Data Lakes. Microsoft’s next option is called Azure Data Lake Services (ADLS), and it seems to be the company’s favored long-term solution to its D365 F&SCM reporting challenge. Data lake” is a generic term that refers to a fairly new development in the world of big data analytics.

Data Lake 52

Data Lake Unstructured Data Reporting Finance 52

Alation

FEBRUARY 20, 2020

Organizations who are so successful in their adoption of self-service analytics, that their own business intelligence (BI) evangelists worry that they’ve created an analytics “wild west.” When they see a data catalog for the first time, they’re thrilled that a product exists that can govern the west and increase analyst productivity.

Marketing 52

Marketing Data Lake Dashboards Business Intelligence 52

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 90

Data Warehouse Data Lake Analytics Data Science 90

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 89

Data Analytics Analytics Data Warehouse Data Lake 89

Jet Global

DECEMBER 3, 2021

The term “ business intelligence ” (BI) has been in common use for several decades now, referring initially to the OLAP systems that drew largely upon pre-processed information stored in data warehouses. Thanks to a real-time BI dashboard, you suddenly notice a spate of orders that are coming in with a gross margin of less than 5%.

Business Intelligence 52

Business Intelligence Sales OLAP Data Warehouse 52

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. The email is formatted via HTML output that provides tables for the aggregated job run data.

Reporting 68

Reporting Metrics Optimization Data Lake 68

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

Peter James Thomas

APRIL 3, 2020

Some espouse the opinion that the term is synonymous with Dashboards. Jane opened up her personal dashboard, which already showed the headline figures the CFO had been citing. Some charts or tables may be replicated across a number of dashboards, but others with be specific to a particular area of the business.

Dashboards 61

Dashboards Reporting Sales Data Lake 61