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

Cloudera

MAY 15, 2019

Barbara Eckman from Comcast is another keynote speaker, and is also presenting a breakout session about Comcast’s streaming data platform. The platform comprises ingest, transformation, and storage services in the public cloud, and on-prem RDBMS’s, EDW’s, and a large, ungoverned legacy data lake. American Water.

Enterprise 50

Enterprise Data Lake Data mining IoT 50

DataKitchen

JULY 27, 2023

Here are a few examples that we have seen of how this can be done: Batch ETL with Azure Data Factory and Azure Databricks: In this pattern, Azure Data Factory is used to orchestrate and schedule batch ETL processes. Azure Blob Storage serves as the data lake to store raw data. So go ahead.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

NOVEMBER 14, 2023

Ten years ago, we launched Amazon Kinesis Data Streams , the first cloud-native serverless streaming data service, to serve as the backbone for companies, to move data across system boundaries, breaking data silos. Next, let’s go back to the NHL use case where they combine IoT, data streaming, and machine learning.

IoT 55

IoT Data-driven Data Lake Data Strategy 55

FineReport

APRIL 11, 2023

Free Download of FineReport What is Business Intelligence Dashboard (BI Dashboard)？ A business intelligence dashboard, also known as a BI dashboard, is a tool that presents important business metrics and data points in a visual and analytical format on a single screen.

Dashboards 40

Dashboards Business Intelligence Cost-Benefit Metrics 40

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

CIO Business Intelligence

JUNE 7, 2023

Like the NFL, the NBA CTO opted to partner with Microsoft to leverage its Azure cloud platform, which Bhagavathula says contained all the digital components necessary to build the association’s streaming platform, while providing a cloud data lake and machine learning models the NBA could capitalize on for next-generation applications.

Digital Transformation 52

Digital Transformation Recreation/Entertainment Machine Learning Data Lake 52

AWS Big Data

FEBRUARY 21, 2023

Regardless of the division or use case it is related to, dimensional data models can be used to store data obtained from tracking various processes like patient encounters, provider practice metrics, aftercare surveys, and more. Although data lakes resemble data vaults, a data vault provides more features of a data warehouse.

Data Warehouse 65

Data Warehouse Data Lake Cost-Benefit Metadata 65

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Alation

AUGUST 2, 2022

Establishing and monitoring metrics that validate improvements. Customer centricity requires modernized data and IT infrastructures. Too often, companies manage data in spreadsheets or individual databases. This means that you’re likely missing valuable insights that could be gleaned from data lakes and data analytics.

Strategy 52

Strategy Cost-Benefit Metrics Data Lake 52

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52