AWS Big Data

MARCH 25, 2024

Stream processing, however, can enable the chatbot to access real-time data and adapt to changes in availability and price, providing the best guidance to the customer and enhancing the customer experience. When the model finds an anomaly or abnormal metric value, it should immediately produce an alert and notify the operator.

Data Lake 121

Data Lake Unstructured Data Management Snapshot 121

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 96

Analytics Data Warehouse Data Lake Metadata 96

Cloudera

MAY 23, 2024

In modern enterprises, the exponential growth of data means organizational knowledge is distributed across multiple formats, ranging from structured data stores such as data warehouses to multi-format data stores like data lakes.

Management 80

Management Metrics Data Processing Machine Learning 80

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 115

Cost-Benefit Metadata Structured Data Data-driven 115

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 111

Testing Data Warehouse Metrics Cost-Benefit 111

IBM Big Data Hub

APRIL 9, 2024

This allows the Masters to scale analytics and AI wherever their data resides, through open formats and integration with existing databases and tools. “Hole distances and pin positions vary from round to round and year to year; these factors are important as we stage the data.” ” Watsonx.ai

Management 78

Management IT Machine Learning Metrics 78

AWS Big Data

NOVEMBER 9, 2023

Third-party APIs – These provide analytics and survey data related to ecommerce websites. This could include details like traffic metrics, user behavior, conversion rates, customer feedback, and more. Flat files – Other systems supply data in the form of flat files of different formats.

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

AWS Big Data

MARCH 26, 2024

The following figure shows some of the metrics derived from the study. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud. Learn from this to build querying capabilities across your data lake and the data warehouse.

Data Strategy 98

Data Strategy Strategy Data Warehouse Prescriptive Analytics 98

AWS Big Data

APRIL 19, 2023

Building an optimal data system As data grows at an extraordinary rate, data proliferation across your data stores, data warehouse, and data lakes can become a challenge. This performance innovation allows Nasdaq to have a multi-use data lake between teams.

Data Warehouse 59

Data Warehouse Data Lake Unstructured Data Optimization 59

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

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

AWS Big Data

JANUARY 22, 2024

The success of the implementation meant assessing various aspects of the data infrastructure, data management, and business outcomes. They classified the metrics and indicators in the following categories: Data usage – A clear understanding of who is consuming what data source, materialized with a mapping of consumers and producers.

Data-driven 117

Data-driven Advertising Metadata Data Architecture 117

CIO Business Intelligence

DECEMBER 4, 2023

Once focused solely on reducing search and retrieval times, information lifecycle management (ILM) is now critical to workflow automation, identifying and tracking performance metrics, and harnessing the burgeoning potential of AI. Operationalizing data to drive revenue CIOs report that their roles are rising in importance and impact.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

Alation

JULY 19, 2022

Historically restricted to the purview of data engineers, data quality information is essential for all user groups to see. Finally, data catalogs can help data scientists promulgate the results of their projects. Data scientists often have different requirements for a data catalog than data analysts.

Metadata 59

Metadata Data Quality Statistics Data Science 59

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

AWS Big Data

JULY 12, 2023

Amazon Redshift helps you break down the data silos and allows you to run unified, self-service, real-time, and predictive analytics on all data across your operational databases, data lake, data warehouse, and third-party datasets with built-in governance.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

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 98

Data Lake IoT Metadata Testing 98

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. Mengchu currently works on query optimization and data lake query performance.

Statistics 108

Statistics Data Warehouse Metadata Data Lake 108

BI-Survey

FEBRUARY 27, 2025

Leading-edge: Does it provide data quality or anomaly detection features to enrich metadata with quality metrics and insights, proactively identifying potential issues? Basic: Does the catalog recognize and register unstructured data sources, such as data lakes or document storage systems?

Unstructured Data 52

Unstructured Data Metadata Data Quality Data Governance 52

CIO Business Intelligence

APRIL 16, 2025

But what kind of data do you need for a solid use case? We used to need structured data because our machine learning models expected field-level information. Today, we dont care if the data is structured because we can ingest it all, whether images, recordings, documents, PDF files, or large data lakes.

ROI 71

ROI Measurement Testing Data Lake 71