AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 78

Analytics Data Warehouse Data Lake Metadata 78

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

APRIL 11, 2023

Such a solution should use the latest technologies, including Internet of Things (IoT) sensors, cloud computing, and machine learning (ML), to provide accurate, timely, and actionable data. To take advantage of this data and build an effective inventory management and forecasting solution, retailers can use a range of AWS services.

Forecasting 83

Forecasting Management IoT Data-driven 83

AWS Big Data

AUGUST 1, 2024

The success criteria are the key performance indicators (KPIs) for each component of the data workflow. This includes the ETL processes that capture source data, the functional refinement and creation of data products, the aggregation for business metrics, and the consumption from analytics, business intelligence (BI), and ML.

Data Warehouse 99

Data Warehouse KPI Optimization Cost-Benefit 99

AWS Big Data

FEBRUARY 6, 2023

Let’s look at some key metrics. After analyzing YARN logs by various metrics, you’re ready to design future EMR architectures. He helps customers innovate their business with AWS Analytics, IoT, and AI/ML services. Jiseong Kim is a Senior Data Architect at AWS ProServe.

Dashboards 83

Dashboards Optimization Data Lake Cost-Benefit 83

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

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

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 59

IoT Data-driven Data Lake Data Strategy 59

CIO Business Intelligence

APRIL 11, 2022

billion connected Internet of Things (IoT) devices by 2025, generating almost 80 billion zettabytes of data at the edge. This next manifestation of centralized data strategy emanates from past experiences with trying to coalesce the enterprise around a large-scale monolithic data lake. over last year.

Optimization 52

Optimization Data Lake Internet of Things Data Strategy 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

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 70

Data Warehouse Data Lake Cost-Benefit Metadata 70

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 Metrics Cost-Benefit 40

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.

Cost-Benefit 52

Cost-Benefit Metrics Strategy Data Lake 52

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

JULY 17, 2024

In this blog post, we delve into the intricacies of building a reliable data analytics pipeline that can scale to accommodate millions of vehicles, each generating hundreds of metrics every second using Amazon OpenSearch Ingestion. OpenSearch Ingestion provides a fully managed serverless integration to tap into these data streams.

Analytics 104

Analytics IoT Dashboards Data Lake 104

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 Data-driven 150

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

AWS Big Data

DECEMBER 19, 2024

Data lakes were originally designed to store large volumes of raw, unstructured, or semi-structured data at a low cost, primarily serving big data and analytics use cases. Enabling automatic compaction on Iceberg tables reduces metadata overhead on your Iceberg tables and improves query performance.

Data Lake 91

Data Lake IoT Metadata Testing 91

CIO Business Intelligence

OCTOBER 30, 2024

We’ve rolled out the foundational version of digital manufacturing to all the plants, which is a single platform data lake with contextualization. All the equipment at the plants, including the P&IDs and drawings, are contextualized in this data lake. What approach are you taking to ensure ROI on these investments?

Digital Transformation 118

Digital Transformation Manufacturing IT Data Lake 118

AWS Big Data

OCTOBER 25, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. It also helps you securely access your data in operational databases, data lakes, or third-party datasets with minimal movement or copying of data.

Statistics 87

Statistics Data Warehouse Metadata Data Lake 87

CIO Business Intelligence

FEBRUARY 18, 2025

If you reflect for a moment, the last major technology inflection points were probably things like mobility, IoT, development operations and the cloud to name but a few. Inputs to the tasks could be the location of products and performance metrics and a CRM system for customer contact information.

Machine Learning 90

Machine Learning Data Quality Enterprise Sales 90