AWS Big Data

DECEMBER 12, 2024

One-time and complex queries are two common scenarios in enterprise data analytics. Complex queries, on the other hand, refer to large-scale data processing and in-depth analysis based on petabyte-level data warehouses in massive data scenarios. Here, data modeling uses dbt on Amazon Redshift.

Snapshot 97

Snapshot Recreation/Entertainment Experimentation Data Lake 97

AWS Big Data

JANUARY 6, 2025

Amazon AppFlow is a fully managed integration service that you can use to securely transfer data from software as a service (SaaS) applications, such as Google BigQuery, Salesforce, SAP, HubSpot, and ServiceNow, to Amazon Web Services (AWS) services such as Amazon Simple Storage Service (Amazon S3) and Amazon Redshift, in just a few clicks.

Analytics 98

Analytics Data Warehouse Metrics Big Data 98

CIO Business Intelligence

DECEMBER 11, 2024

They must also select the data processing frameworks such as Spark, Beam or SQL-based processing and choose tools for ML. Based on business needs and the nature of the data, raw vs structured, organizations should determine whether to set up a data warehouse, a Lakehouse or consider a data fabric technology.

Management 111

Management Data Governance Data Science Reporting 111

AWS Big Data

JUNE 29, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud that delivers powerful and secure insights on all your data with the best price-performance. With Amazon Redshift, you can analyze your data to derive holistic insights about your business and your customers.

Data Warehouse 83

Data Warehouse Dashboards Testing Visualization 83

AWS Big Data

DECEMBER 4, 2024

With this new functionality, customers can create up-to-date replicas of their data from applications such as Salesforce, ServiceNow, and Zendesk in an Amazon SageMaker Lakehouse and Amazon Redshift. SageMaker Lakehouse gives you the flexibility to access and query your data in-place with all Apache Iceberg compatible tools and engines.

Data Integration 114

Data Integration Data Lake Statistics Data-driven 114

AWS Big Data

JUNE 29, 2023

Amazon Kinesis Data Analytics makes it easy to transform and analyze streaming data in real time. In this post, we discuss why AWS recommends moving from Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics for Apache Flink to take advantage of Apache Flink’s advanced streaming capabilities.

Data Analytics 103

Data Analytics Analytics IoT Data Lake 103

AWS Big Data

JANUARY 15, 2025

In addition to real-time analytics and visualization, the data needs to be shared for long-term data analytics and machine learning applications. AWS Database Migration Service (AWS DMS) is used to securely transfer the relevant data to a central Amazon Redshift cluster.

IoT 111

IoT Machine Learning Metadata Data-driven 111

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 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

CIO Business Intelligence

APRIL 5, 2022

Investment in data warehouses is rapidly rising, projected to reach $51.18 billion by 2028 as the technology becomes a vital cog for enterprises seeking to be more data-driven by using advanced analytics. Data warehouses are, of course, no new concept. More data, more demanding. “As

Data Warehouse 98

Data Warehouse Visualization Data-driven Data Architecture 98

AWS Big Data

FEBRUARY 26, 2025

This premier event showcased groundbreaking advancements, keynotes from AWS leadership, hands-on technical sessions, and exciting product launches. Analytics remained one of the key focus areas this year, with significant updates and innovations aimed at helping businesses harness their data more efficiently and accelerate insights.

Analytics 61

Analytics Data Lake Metadata Data Warehouse 61

CIO Business Intelligence

SEPTEMBER 10, 2022

Poonam Mohan, vice president of corporate technology at American Airlines, oversees many of the airline’s AI and data analytics initiatives and has been fundamental to implementing Leibman’s vision. We moved our major data platforms to the cloud and implemented data hubs for Customer and Operations,” Mohan says. “We

Analytics 145

Analytics Machine Learning Data Warehouse Data-driven 145

AWS Big Data

AUGUST 13, 2024

In this blog post, we explore how to use the SFTP Connector for AWS Glue from the AWS Marketplace to efficiently process data from Secure File Transfer Protocol (SFTP) servers into Amazon Simple Storage Service (Amazon S3) , further empowering your data analytics and insights. The following diagram illustrates this architecture.

Data Processing 115

Data Processing Visualization Data Lake Data Processing 115

CIO Business Intelligence

JUNE 29, 2022

And as businesses contend with increasingly large amounts of data, the cloud is fast becoming the logical place where analytics work gets done. For many enterprises, Microsoft Azure has become a central hub for analytics. Azure Data Factory. Azure Data Explorer. Azure Data Lake Analytics.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

Smart Data Collective

OCTOBER 13, 2021

If we talk about Big Data, data visualization is crucial to more successfully drive high-level decision making. Big Data analytics has immense potential to help companies in decision making and position the company for a realistic future. There is little use for data analytics without the right visualization tool.

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

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 116

Data Warehouse Snapshot Data Processing Internet of Things 116

Sisense

MARCH 6, 2019

The BI industry takes Gartner’s perspective very seriously, and year after year, it’s very common to see messages that were first described in the Gartner summits making their way into the websites of many analytics vendors. The crowd who attends these events are made mostly of analytics leaders in Enterprises.

Data Analytics 75

Data Analytics Analytics Experimentation Data-driven 75

AWS Big Data

OCTOBER 23, 2024

Amazon Redshift is a fully managed cloud data warehouse that’s used by tens of thousands of customers for price-performance, scale, and advanced data analytics. Getir’s data analytics environment encompasses hundreds of terabytes of data, thousands of tables, and billions upon billions of data rows.

Data Warehouse 111

Data Warehouse Cost-Benefit Data Lake Data-driven 111

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 134

Analytics IoT Data-driven Snapshot 134

AWS Big Data

APRIL 10, 2024

and zero-ETL support) as the source, and a Redshift data warehouse as the target. The integration replicates data from the source database into the target data warehouse. Additionally, you can choose the capacity, to limit the compute resources of the data warehouse. For this post, set this to 8 RPUs.

Data Warehouse 119

Data Warehouse Analytics Metrics Snapshot 119

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 111

Data Warehouse Analytics Data Lake Data Science 111

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. We leverage the power of Snowflake to advance the correlation of events as you scale data ingestion.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

AWS Big Data

MAY 16, 2024

As technology continues to evolve, one specific facet of this journey is reaching unprecedented proportions: geospatial data. With Amazon Redshift, you can get real-time insights and predictive analytics on all of your data across your operational databases, data lake, data warehouse, and third-party datasets.

Data Warehouse 119

Data Warehouse Visualization Cost-Benefit Data-driven 119

AWS Big Data

OCTOBER 10, 2024

Amazon Redshift has established itself as a highly scalable, fully managed cloud data warehouse trusted by tens of thousands of customers for its superior price-performance and advanced data analytics capabilities. This allows you to maintain a comprehensive view of your data while optimizing for cost-efficiency.

Data Lake 120

Data Lake Data Warehouse Recreation/Entertainment Data-driven 120

AWS Big Data

MAY 17, 2023

During that same time, AWS has been focused on helping customers manage their ever-growing volumes of data with tools like Amazon Redshift , the first fully managed, petabyte-scale cloud data warehouse. One group performed extract, transform, and load (ETL) operations to take raw data and make it available for analysis.

Data Warehouse 126

Data Warehouse Cost-Benefit Sales Data-driven 126

AWS Big Data

SEPTEMBER 11, 2024

Source systems Aruba’s source repository includes data from three different operating regions in AMER, EMEA, and APJ, along with one worldwide (WW) data pipeline from varied sources like SAP S/4 HANA, Salesforce, Enterprise Data Warehouse (EDW), Enterprise Analytics Platform (EAP) SharePoint, and more.

Data Architecture 111

Data Architecture Optimization Data Warehouse Metadata 111

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

DECEMBER 8, 2023

More and more of FanDuel’s community of analysts and business users looked for comprehensive data solutions that centralized the data across the various arms of their business. Their individual, product-specific, and often on-premises data warehouses soon became obsolete.

Data Warehouse 97

Data Warehouse Cost-Benefit KPI Risk 97

AWS Big Data

JUNE 28, 2023

There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (e.g. With Aurora zero-ETL integration with Amazon Redshift, the integration replicates data from the source database into the target data warehouse. or higher version) database.

Data Warehouse 105

Data Warehouse Analytics Metrics Dashboards 105

AWS Big Data

MAY 28, 2024

Before we dive in, we recommend reviewing Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1 for the basic functionalities of Kinesis Data Streams. Part 1 also contains architectural examples for building real-time applications for time series data and event-sourcing microservices.

IoT 115

IoT Analytics Dashboards Data-driven 115

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation. Reference data management.

Management 97

Management Data Warehouse Digital Transformation Dashboards 97

AWS Big Data

DECEMBER 4, 2024

These nodes can implement analytical platforms like data lake houses, data warehouses, or data marts, all united by producing data products. Education and enablement – Conduct learning interventions to upskill teams on understanding and using the data as a product approach.

Metadata 105

Metadata Data Governance Data Quality Data-driven 105

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 115

Data Lake Data Warehouse Data-driven B2B 115

AWS Big Data

FEBRUARY 1, 2024

This stack creates the following resources and necessary permissions to integrate the services: Data stream – With Amazon Kinesis Data Streams , you can send data from your streaming source to a data stream to ingest the data into a Redshift data warehouse. version cluster. version cluster.

Data Warehouse 134

Data Warehouse Dashboards Risk Management Risk 134

AWS Big Data

NOVEMBER 8, 2023

Scaling serverless data processing with Amazon Kinesis and Apache Kafka: Explore how to build scalable data processing applications using AWS Lambda. Learn practical insights into integrating Lambda with Amazon Kinesis and Apache Kafka using their event-driven models for real-time data streaming and processing.

Data-driven 105

Data-driven Machine Learning Data Lake Cost-Benefit 105

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 105

Data Warehouse Testing Data Lake Data-driven 105

Cloudera

DECEMBER 12, 2018

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks.

Data Warehouse 42

Data Warehouse Marketing Big Data Data-driven 42

Smart Data Collective

NOVEMBER 18, 2020

Complex mathematical algorithms are used to segment data and estimate the likelihood of subsequent events. Every Data Scientist needs to know Data Mining as well, but about this moment we will talk a bit later. Where to Use Data Science? Where to Use Data Mining? Data Mining is an important research process.

Data mining 144

Data mining Data Science Informatics Statistics 144