Dataconomy

JUNE 18, 2025

Common use cases for data integration Data integration demonstrates its value across a variety of applications. Feeding data for analytics Integrated data is essential for populating data warehouses, data lakes, and lakehouses, ensuring that analysts have access to complete datasets for their work.

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Data Warehouse Data Silos ETL Big Data 91

AWS Machine Learning Blog

NOVEMBER 15, 2023

They are processing data across channels, including recorded contact center interactions, emails, chat and other digital channels. Solution requirements Principal provides investment services through Genesys Cloud CX, a cloud-based contact center that provides powerful, native integrations with AWS.

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AWS Analytics Analytics ML 117

AWS Machine Learning Blog

AUGUST 8, 2024

As one of the largest AWS customers, Twilio engages with data, artificial intelligence (AI), and machine learning (ML) services to run their daily workloads. Data is the foundational layer for all generative AI and ML applications. The following diagram illustrates the solution architecture.

SQL 126

SQL Data Lakes Data Analyst AWS 126

Smart Data Collective

AUGUST 17, 2022

You can safely use an Apache Kafka cluster for seamless data movement from the on-premise hardware solution to the data lake using various cloud services like Amazon’s S3 and others. It will enable you to quickly transform and load the data results into Amazon S3 data lakes or JDBC data stores.

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IBM Journey to AI blog

MARCH 14, 2024

Such infrastructure should not only address these issues but also scale according to the demands of AI workloads, thereby enhancing business outcomes. Native integrations with IBM’s data fabric architecture on AWS establish a trusted data foundation, facilitating the acceleration and scaling of AI across the hybrid cloud.

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AWS Database ETL AI 93

phData

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

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Data Lakes Data Models Data Modeling Data Warehouse 52

AWS Machine Learning Blog

JUNE 25, 2024

To create and share customer feedback analysis without the need to manage underlying infrastructure, Amazon QuickSight provides a straightforward way to build visualizations, perform one-time analysis, and quickly gain business insights from customer feedback, anytime and on any device. The Step Functions workflow starts.

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AWS Natural Language Processing Machine Learning Machine Learning 126

Flipboard

MAY 9, 2025

This pattern creates a comprehensive solution that transforms raw social media data into actionable business intelligence (BI) through advanced AI capabilities. 3B Instruct Amazon Bedrock, the system provides tailored marketing content that adds business value. By integrating LLMs such as Anthropics Claude 3.5

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Dataconomy

SEPTEMBER 4, 2023

Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence. Ensure that data is clean, consistent, and up-to-date.

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Analytics Analytics Big Data Analytics Big Data Analytics 203

ODSC - Open Data Science

APRIL 25, 2025

Unfortunately, the current landscape of our consuming systems, especially business intelligence tools, just wont work withAPIs. He is the founder of Data Futures, a consultancy focused on cloud-native data modernization, and an AWS DataHero.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

AWS Machine Learning Blog

APRIL 12, 2023

In this post, we describe how AWS Partner Airis Solutions used Amazon Lookout for Equipment , AWS Internet of Things (IoT) services, and CloudRail sensor technologies to provide a state-of-the-art solution to address these challenges. It’s an easy way to run analytics on IoT data to gain accurate insights.

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Women in Big Data

NOVEMBER 27, 2024

By maintaining historical data from disparate locations, a data warehouse creates a foundation for trend analysis and strategic decision-making. How to Choose a Data Warehouse for Your Big Data Choosing a data warehouse for big data storage necessitates a thorough assessment of your unique requirements.

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Data Warehouse Big Data Big Data Azure 59

IBM Journey to AI blog

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

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Data Lakes Data Warehouse Azure Apache Hadoop 52

Pickl AI

FEBRUARY 23, 2025

Amazon EMR (Elastic MapReduce) Amazon EMR is a cloud-native Big Data platform that simplifies running Big Data frameworks such as Apache Hadoop and Apache Spark on AWS. Statistics : According to AWS reports, EMR reduces the time required for Big Data processing tasks by up to 90% compared to traditional methods.

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Big Data Big Data Apache Hadoop Apache Kafka 52

Pickl AI

OCTOBER 10, 2024

Inconsistent or unstructured data can lead to faulty insights, so transformation helps standardise data, ensuring it aligns with the requirements of Analytics, Machine Learning , or Business Intelligence tools. This makes drawing actionable insights, spotting patterns, and making data-driven decisions easier.

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

Pickl AI

APRIL 9, 2025

Loading : Storing the transformed data in a target system like a data warehouse, data lake, or even a database. This stage involves optimizing the data for querying and analysis. Data Loading : Mechanisms for storing processed data in warehouses or lakes, ensuring optimal performance for querying and analysis.

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ETL Data Warehouse AWS Business Intelligence 52

Tableau

DECEMBER 7, 2022

Cut costs by consolidating data warehouse investments. Think of Tableau as your data visualization and business intelligence layer on top of Genie—allowing you to see, understand, and act on your live customer data. Built-in connectors bring in data from every single channel. Bring your own AI with AWS.

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Tableau Data Warehouse Data Pipeline Data Visualization 98

Tableau

DECEMBER 7, 2022

Cut costs by consolidating data warehouse investments. Think of Tableau as your data visualization and business intelligence layer on top of Genie—allowing you to see, understand, and act on your live customer data. Built-in connectors bring in data from every single channel. Bring your own AI with AWS.

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Tableau Data Warehouse Data Pipeline Data Visualization 98

IBM Journey to AI blog

JULY 17, 2023

Watsonx.data is built on 3 core integrated components: multiple query engines, a catalog that keeps track of metadata, and storage and relational data sources which the query engines directly access. AMC Networks is excited by the opportunity to capitalize on the value of all of their data to improve viewer experiences.

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AI AI Machine Learning Machine Learning 74

Precisely

JANUARY 25, 2024

There are three potential approaches to mainframe modernization: Data Replication creates a duplicate copy of mainframe data in a cloud data warehouse or data lake, enabling high-performance analytics virtually in real time, without negatively impacting mainframe performance.

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Data Governance Database Cloud Data Data Lakes 69

IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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Data Warehouse Cloud Data Analytics Analytics 58

Alation

APRIL 7, 2021

Powered by the industry’s broadest and deepest connectivity, the Alation Data Catalog supports data intelligence use cases across an organization’s de facto hybrid cloud environments. Alation Cloud Service is available on AWS. Three core capabilities of a data catalog. Not all data catalogs are created equal.

Data Governance 52

Data Governance Data Silos AWS Data Lakes 52

DagsHub

NOVEMBER 11, 2024

These processes are essential in AI-based big data analytics and decision-making. Data Lakes Data lakes are crucial in effectively handling unstructured data for AI applications. They serve as centralized repositories where raw data, whether structured or unstructured, can be stored in its native format.

AI 52

AI AI Data Lakes Database 52

Tableau

DECEMBER 7, 2022

Think of Tableau as your data visualization and business intelligence layer on top of Data Cloud—allowing you to see, understand, and act on your live customer data. These features cover functionality for enterprise customer data in five key categories: Connect, Harmonize, Unify, Analyze and Predict, and Act.

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Tableau Data Warehouse Data Pipeline Data Visualization 55

Alation

JUNE 7, 2023

Airlines Reporting Corporation (ARC) used self-service data access as a way to accelerate time-to-market for new products. It also sells business intelligence and other data products to travel industry customers, and with over 50 years’ worth of data, they have a lot of insights to offer.

Data Silos 52

Data Silos Data Lakes Data Governance Business Intelligence 52

ODSC - Open Data Science

JANUARY 18, 2024

So as you take inventory of your existing skill set, you’ll want to start to identify the areas where you need to focus on to become a data engineer. These areas may include SQL, database design, data warehousing, distributed systems, cloud platforms (AWS, Azure, GCP), and data pipelines. Learn more about the cloud.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

The MLOps Blog

MAY 17, 2023

A data pipeline is created with the focus of transferring data from a variety of sources into a data warehouse. Further processes or workflows can then easily utilize this data to create business intelligence and analytics solutions. This involves looking at the data structure, relationships, and content.

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ETL Data Pipeline ML ML 59

Dataversity

MARCH 29, 2021

It has taken a global pandemic for organizations to finally realize that the old way of doing businesses – and the legacy technologies and processes that came with it – are no longer going to cut it. The post The Move to Public Cloud and an Intelligent Data Strategy appeared first on DATAVERSITY. As […].

DataOps 94

DataOps Data Lakes Azure Cloud Data 94

Alation

MARCH 21, 2023

Having been in business for over 50 years, ARC had accumulated a massive amount of data that was stored in siloed, on-premises servers across its 7 business domains. Using Alation, ARC automated the data curation and cataloging process. “So

Analytics 52

Analytics Analytics Data Silos Big Data 52

Data Science Blog

FEBRUARY 7, 2023

Das Format Business Talk am Kudamm in Berlin führte ein Interview mit Benjamin Aunkofer zum Thema “Business Intelligence und Process Mining nachhaltig umsetzen”. Für Data Science ja sowieso. 3 – Bei der Nutzung von Daten fallen oft die Begriffe „Process Mining“ und „Business Intelligence“.

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Business Intelligence Business Intelligence Data Warehouse Data Lakes 286

The MLOps Blog

MARCH 21, 2023

Other users Some other users you may encounter include: Data engineers , if the data platform is not particularly separate from the ML platform. Analytics engineers and data analysts , if you need to integrate third-party business intelligence tools and the data platform, is not separate.

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Machine Learning Machine Learning Data Scientist ML 69

Flipboard

DECEMBER 4, 2024

The use of separate data warehouses and lakes has created data silos, leading to problems such as lack of interoperability, duplicate governance efforts, complex architectures, and slower time to value. You can use Amazon SageMaker Lakehouse to achieve unified access to data in both data warehouses and data lakes.

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Data Lakes Data Warehouse AWS Database 137

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Die Definition eines Data Lakehouse Ein Data Lakehouse ist eine moderne Datenspeicher- und -verarbeitungsarchitektur, die die Vorteile von Data Lakes und Data Warehouses vereint.

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Data Warehouse Data Lakes Azure AWS 147

Flipboard

MAY 15, 2025

Data environments in data-driven organizations are changing to meet the growing demands for analytics , including business intelligence (BI) dashboarding, one-time querying, data science , machine learning (ML), and generative AI. and higher, and AWS Glue 5.0 and higher, and AWS Glue 5.0.

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AWS SQL Data Lakes Data Warehouse 135

AWS Machine Learning Blog

OCTOBER 11, 2024

It uses Amazon Bedrock , AWS Health , AWS Step Functions , and other AWS services. Some examples of AWS-sourced operational events include: AWS Health events — Notifications related to AWS service availability, operational issues, or scheduled maintenance that might affect your AWS resources.

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AWS AI AI Data Lakes 97