AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift enables you to use SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and machine learning (ML) to deliver the best price-performance at scale.

Data Warehouse 94

Data Warehouse Data Lake Analytics Data Science 94

CIO Business Intelligence

APRIL 4, 2023

Businesses that lead in fully deploying AI will be able to optimize customer experiences and efficiencies that help maximize customer retention and customer acquisition and gain a distinct advantage over the competition. Constructing the right data architecture cannot be bypassed. Tolkien intimated, anything worth achieving takes time.

Data Architecture 52

Data Architecture Data Lake Data Warehouse Cost-Benefit 52

CIO Business Intelligence

MARCH 6, 2023

When you store and deliver data at Shutterstock’s scale, the flexibility and elasticity of the cloud is a huge win, freeing you from the burden of costly, high-maintenance data centers. Then coupling with AWS’ strong authentication mechanisms, we can say with certainty that we have security and restrictions around who can access data.”

Data Lake 58

Data Lake Cost-Benefit Recreation/Entertainment Experimentation 58

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

OCTOBER 2, 2023

JSON data in Amazon Redshift Amazon Redshift enables storage, processing, and analytics on JSON data through the SUPER data type, PartiQL language, materialized views, and data lake queries. The function JSON_PARSE allows you to extract the binary data in the stream and convert it into the SUPER data type.

Cost-Benefit 87

Cost-Benefit Metadata Structured Data Management 87

AWS Big Data

MARCH 25, 2024

Both engines provide native ingestion support from Kinesis Data Streams and Amazon MSK via a separate streaming pipeline to a data lake or data warehouse for analysis. For more details, refer to Create a low-latency source-to-data lake pipeline using Amazon MSK Connect, Apache Flink, and Apache Hudi.

Data Lake 91

Data Lake Unstructured Data Management Modeling 91

AWS Big Data

MARCH 27, 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. Complete the implementation tasks such as data ingestion and performance testing.

Testing 100

Testing Data Warehouse Metrics Cost-Benefit 100

AWS Big Data

MARCH 26, 2024

The following diagram illustrates the different pipelines to ingest data from various source systems using AWS services. Data storage Structured, semi-structured, or unstructured batch data is stored in an object storage because these are cost-efficient and durable.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

FineReport

APRIL 11, 2023

Every user can now create interactive reports and utilize data visualization to disseminate knowledge to both internal and external stakeholders. In this article, we will explore what BI Dashboard is, its key features, benefits and limitations, and best practices and examples.

Dashboards 40

Dashboards Business Intelligence Cost-Benefit Metrics 40

Sisense

JUNE 30, 2020

Using predictive analytics, organizations can plan for forthcoming scenarios, anticipate new trends, and prepare for them most efficiently and cost-effectively. Predicting forthcoming trends sets the stage for optimizing the benefits your organization takes from them. Using visualizations to make smarter decisions.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

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

OCTOBER 7, 2021

Within the context of a data mesh architecture, I will present industry settings / use cases where the particular architecture is relevant and highlight the business value that it delivers against business and technology areas. When it comes to data movement outside the boundaries of Data Products (i.e., A Client Example.

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

Corinium

APRIL 25, 2019

Most enterprises in the 21st century regard data as an incredibly valuable asset – Insurance is no exception - to know your customers better, know your market better, operate more efficiently and other business benefits. In data-driven organizations, data is flowing. But I’ll give an example in favour of each.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

BizAcuity

MARCH 1, 2019

Traditional methods of analyzing structured data are not designed to efficiently process these large amounts of real-time data that is collected from IoT devices. This is where AI-based analysis and response play a critical role in extracting optimal value from the data. IoT produces a treasure trove of big data.

IoT 56

IoT Internet of Things Big Data Data-driven 56

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52