CIO Business Intelligence

MAY 21, 2024

Real-Time Intelligence, on the other hand, takes that further by supporting data in AWS, Google Cloud Platform, Kafka installations, and on-prem installations. “We We introduced the Real-Time Hub,” says Arun Ulagaratchagan, CVP, Azure Data at Microsoft. You can monitor and act on the data and you can set thresholds.”

Broadcasting 126

Broadcasting Recreation/Entertainment Manufacturing Data Lake 126

AWS Big Data

JANUARY 8, 2024

In the subsequent post in our series, we will explore the architectural patterns in building streaming pipelines for real-time BI dashboards, contact center agent, ledger data, personalized real-time recommendation, log analytics, IoT data, Change Data Capture, and real-time marketing data.

Analytics 134

Analytics IoT Data-driven Snapshot 134

AWS Big Data

SEPTEMBER 5, 2024

Amazon Redshift , a warehousing service, offers a variety of options for ingesting data from diverse sources into its high-performance, scalable environment. In this example, we use Amazon MSK as the streaming source for IoT telemetry data. example.com:9092,broker-2.example.com:9092' example.com:9092,broker-2.example.com:9092'

IoT 111

IoT Data Warehouse Cost-Benefit Reporting 111

BizAcuity

NOVEMBER 22, 2022

In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes.

Data Warehouse 98

Data Warehouse Cost-Benefit Data Lake Internet of Things 98

Cloudera

JANUARY 30, 2024

According to Gartner , 80 percent of manufacturing CEOs are increasing investments in digital technologies—led by artificial intelligence (AI), Internet of Things (IoT), data, and analytics. Manufacturers now have unprecedented capacity to collect, utilize, and manage massive amounts of data. Eliminate data silos.

Manufacturing 81

Manufacturing Contextual Data IoT Internet of Things 81

Cloudera

AUGUST 9, 2022

Standby systems can be designed to meet storage requirements during typical periods with burstable compute for failover scenarios using new features such as Data Lake Scaling. Automating the healing, recovery, scaling, and rebalancing of core data services such as our Operational Database. Conclusion.

Data Lake 78

Data Lake Data Warehouse Data-driven IoT 78

CIO Business Intelligence

MAY 12, 2022

The biggest challenge for any big enterprise is organizing the data that has organically grown across the organization over the last several years. Everyone has data lakes, data ponds – whatever you want to call them. How do you get your arms around all the data you have? So, real-time data has become air.

Testing 98

Testing Advertising Data Lake Marketing 98

AWS Big Data

AUGUST 1, 2024

Success criteria alignment by all stakeholders (producers, consumers, operators, auditors) is key for successful transition to a new Amazon Redshift modern data architecture. The success criteria are the key performance indicators (KPIs) for each component of the data workflow.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

AWS Big Data

FEBRUARY 6, 2023

He helps customers innovate their business with AWS Analytics, IoT, and AI/ML services. He has a specialty in big data services and technologies and an interest in building customer business outcomes together. Jiseong Kim is a Senior Data Architect at AWS ProServe. George Zhao is a Senior Data Architect at AWS ProServe.

Dashboards 98

Dashboards Optimization Data Lake Cost-Benefit 98

TDAN

JUNE 16, 2020

When companies embark on a journey of becoming data-driven, usually, this goes hand in and with using new technologies and concepts such as AI and data lakes or Hadoop and IoT. Suddenly, the data warehouse team and their software are not the only ones anymore that turn data […].

Data Warehouse 52

Data Warehouse Data-driven Data Lake IoT 52

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Metadata plays a key role here in discovering the data assets.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Cloudera

DECEMBER 19, 2018

The most common big data use case is data warehouse optimization. Big data architecture is used to augment different applications, operating alongside or in a discrete fashion with a data warehouse. A big data implementation may even replace a data warehouse entirely with a data lake.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

BizAcuity

APRIL 1, 2023

Introduction In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. Using minutes- and seconds-old data for real-time personalization can significantly grow user engagement.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Lake Internet of Things 52

AWS Big Data

FEBRUARY 6, 2023

Refactoring coupled compute and storage to a decoupling architecture is a modern data solution. It enables compute such as EMR instances and storage such as Amazon Simple Storage Service (Amazon S3) data lakes to scale. He helps customers innovate their business with AWS Analytics, IoT, and AI/ML services.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

AWS Big Data

JUNE 7, 2023

Cargotec captures terabytes of IoT telemetry data from their machinery operated by numerous customers across the globe. This data needs to be ingested into a data lake, transformed, and made available for analytics, machine learning (ML), and visualization. In his spare time, he loves to play cricket and badminton.

Metadata 59

Metadata Data Lake Machine Learning Big Data 59

Data Virtualization

JANUARY 20, 2022

Reading Time: 3 minutes We are always focused on making things “Go Fast” but how do we make sure we future proof our data architecture and ensure that we can “Go Far”? Technologies change constantly within organizations and having a flexible architecture is key.

Data Architecture 52

Data Architecture Data Integration Technology Management 52

Data Virtualization

JANUARY 20, 2022

Reading Time: 3 minutes We are always focused on making things “Go Fast” but how do we make sure we future proof our data architecture and ensure that we can “Go Far”? Technologies change constantly within organizations and having a flexible architecture is key.

Data Architecture 52

Data Architecture Data Integration Technology Management 52

Alation

APRIL 14, 2022

For example, data science always consumes “historical” data, and there is no guarantee that the semantics of older datasets are the same, even if their names are unchanged. Pushing data to a data lake and assuming it is ready for use is shortsighted.

Metadata 59

Metadata Data Governance Data-driven Modeling 59

Alation

JULY 7, 2022

In the 2010s, the growing scope of the data landscape gave rise to a new profession: the data scientist. This new role, combined with the creation of data lakes and the increasing use of cloud services, created new employment opportunities in data analytics, data architecture, and data management.

Metadata 52

Metadata Data-driven Insurance Statistics 52

Data Virtualization

JUNE 2, 2023

The post The Energy Utilities Series: Challenges and Opportunities of Decarbonization (Post 2 of 6) appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information. Decarbonization is the process of transitioning from.

Data Integration 52

Data Integration Internet of Things Management Data Lake 52

CIO Business Intelligence

APRIL 23, 2025

Step 1: Data ingestion Identify your data sources. First, list out all the insurance data sources. These include older systems (like underwriting, claims processing and billing) as well as newer streams (like telematics, IoT devices and external APIs). Collect your data in one place.

Insurance 109

Insurance Digital Transformation Data Quality Data Lake 109