AWS Big Data

DECEMBER 17, 2024

Today, Amazon Redshift is used by customers across all industries for a variety of use cases, including data warehouse migration and modernization, near real-time analytics, self-service analytics, data lake analytics, machine learning (ML), and data monetization.

Data Lake 98

Data Lake Data Warehouse Data-driven Optimization 98

CIO Business Intelligence

SEPTEMBER 19, 2024

It will do this, it said, with bidirectional integration between its platform and Salesforce’s to seamlessly delivers data governance and end-to-end lineage within Salesforce Data Cloud. Additional to that, we are also allowing the metadata inside of Alation to be read into these agents.”

Data Governance 123

Data Governance Metadata Unstructured Data Structured Data 123

AWS Big Data

OCTOBER 25, 2023

By some estimates, unstructured data can make up to 80–90% of all new enterprise data and is growing many times faster than structured data. After decades of digitizing everything in your enterprise, you may have an enormous amount of data, but with dormant value. The solution integrates data in three tiers.

Unstructured Data 133

Unstructured Data Metadata Management Analytics 133

Rocket-Powered Data Science

JULY 19, 2023

The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

Smart Data Collective

AUGUST 28, 2021

Data Warehouses and Data Lakes in a Nutshell. A data warehouse is used as a central storage space for large amounts of structured data coming from various sources. On the other hand, data lakes are flexible storages used to store unstructured, semi-structured, or structured raw data.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Structured Data 140

CIO Business Intelligence

MARCH 21, 2022

Data scientists are becoming increasingly important in business, as organizations rely more heavily on data analytics to drive decision-making and lean on automation and machine learning as core components of their IT strategies. Data scientist job description. Semi-structured data falls between the two.

Unstructured Data 137

Unstructured Data Data Analytics Analytics Data Science 137

AWS Big Data

FEBRUARY 29, 2024

The need for an end-to-end strategy for data management and data governance at every step of the journey—from ingesting, storing, and querying data to analyzing, visualizing, and running artificial intelligence (AI) and machine learning (ML) models—continues to be of paramount importance for enterprises.

Data Governance 123

Data Governance Unstructured Data Metadata Data Lake 123

Ontotext

DECEMBER 15, 2022

But whatever their business goals, in order to turn their invisible data into a valuable asset, they need to understand what they have and to be able to efficiently find what they need. Enter metadata. It enables us to make sense of our data because it tells us what it is and how best to use it.

Metadata 52

Metadata Unstructured Data Structured Data Enterprise 52

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. The program must introduce and support standardization of enterprise data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

AWS Big Data

APRIL 2, 2024

Data consumers need detailed descriptions of the business context of a data asset and documentation about its recommended use cases to quickly identify the relevant data for their intended use case. Go to your asset in your data project and choose Generate summary to obtain the detailed description of the asset and its columns.

Metadata 110

Metadata Metrics Data-driven Contextual Data 110

AWS Big Data

FEBRUARY 26, 2025

Amazon SageMaker Introducing the next generation of Amazon SageMaker AWS announces the next generation of Amazon SageMaker, a unified platform for data, analytics, and AI. S3 Metadata is designed to automatically capture metadata from objects as they are uploaded into a bucket, and to make that metadata queryable in a read-only table.

Analytics 62

Analytics Data Lake Metadata Data Warehouse 62

CIO Business Intelligence

MARCH 9, 2022

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

AWS Big Data

SEPTEMBER 12, 2024

AWS services such as Amazon Neptune and Amazon OpenSearch Service form part of their data and analytics pipelines, and AWS Batch is used for long-running data and machine learning (ML) processing tasks. These embeddings, along with metadata such as the document ID and page number, are stored in OpenSearch Service.

Unstructured Data 110

Unstructured Data Metadata Machine Learning Consulting 110

CIO Business Intelligence

SEPTEMBER 12, 2024

Unlike structured data, which fits neatly into databases and tables, etc. I also doubt that all the data your organization owns that’s been strategically stored or piling up is accurate and trustworthy–-nor that you need to invest in making it so if it’s irrelevant and you don’t plan to use it.

Unstructured Data 111

Unstructured Data Deep Learning Metadata Structured Data 111

Cloudera

SEPTEMBER 15, 2022

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Metadata 87

Metadata Big Data Optimization Unstructured Data 87

Cloudera

APRIL 1, 2024

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies.

Unstructured Data 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

Ontotext

JANUARY 10, 2024

Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. No matter what machine learning or graph algorithms are used, they cannot uncover dependencies if the corresponding “signals” are missing.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

CIO Business Intelligence

DECEMBER 13, 2023

Applications such as financial forecasting and customer relationship management brought tremendous benefits to early adopters, even though capabilities were constrained by the structured nature of the data they processed. have encouraged the creation of unstructured data.

Unstructured Data 98

Unstructured Data IoT Metadata Manufacturing 98

AWS Big Data

OCTOBER 1, 2024

Amazon Redshift enables you to efficiently query and retrieve structured and semi-structured data from open format files in Amazon S3 data lake without having to load the data into Amazon Redshift tables. Amazon Redshift extends SQL capabilities to your data lake, enabling you to run analytical queries.

Data Lake 115

Data Lake Statistics Broadcasting Optimization 115

Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 112

IT Data Architecture Unstructured Data Big Data 112

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 114

Cost-Benefit Metadata Structured Data Data-driven 114

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. Data governance Data governance is key to the success of a data hub reference architecture.

Analytics 97

Analytics Data Warehouse Data Lake Metadata 97

BizAcuity

MARCH 29, 2019

Data can be stored as-is, without first structuring it, and different types of analytics can be run on it, from dashboards and visualizations to big data processing, real-time analytics, and machine learning to improve decision making. Deploying Data Lakes in the cloud.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

CIO Business Intelligence

JUNE 23, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 97

IT Data Architecture Unstructured Data Big Data 97

Alation

FEBRUARY 20, 2020

By changing the cost structure of collecting data, it increased the volume of data stored in every organization. Additionally, Hadoop removed the requirement to model or structure data when writing to a physical store.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

Cloudera

MAY 17, 2021

Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform. Beyond there being a number of choices each with very different strengths, the parameters for your decision have also changed.

Data Warehouse 90

Data Warehouse Measurement Reporting Testing 90

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. The third challenge is how to combine data management with analytics. Ontotext Knowledge Graph Platform.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

Ontotext

MAY 26, 2021

In much the same way, in the context of Artificial Intelligence AI systems, the Gold Standard refers to a set of data that has been manually prepared or verified and that represents “the objective truth” as closely as possible. When “reading” unstructured text, AI systems first need to transform it into machine-readable sets of facts.

Data Quality 87

Data Quality Machine Learning Measurement Metadata 87

CIO Business Intelligence

MARCH 6, 2023

We use Snowflake very heavily as our primary data querying engine to cross all of our distributed boundaries because we pull in from structured and non-structured data stores and flat objects that have no structure,” Frazer says. “We think we found a good balance there. Now that’s down to a number of hours.”

Data Lake 88

Data Lake Cost-Benefit Recreation/Entertainment Unstructured Data 88

AWS Big Data

MARCH 26, 2024

This can be achieved using AWS Entity Resolution , which enables using rules and machine learning (ML) techniques to match records and resolve identities. Then, you transform this data into a concise format. Data warehouses can provide a unified, consistent view of a vast amount of customer data for C360 use cases.

Data Strategy 102

Data Strategy Strategy Data Warehouse Prescriptive Analytics 102

Cloudera

NOVEMBER 15, 2024

With flexible schema and partitioning, Iceberg tables can scale to handle petabytes of data while compressing logs to save on storage costs. The metadata-driven approach ensures quick query planning so defenders don’t have to deal with slow processes when they need fast answers.

Analytics 59

Analytics Metadata Snapshot Data-driven 59

Alation

JULY 19, 2022

Across the country, data scientists have an unemployment rate of 2% and command an average salary of nearly $100,000. As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Alation

JUNE 2, 2022

A data catalog is a central hub for XAI and understanding data and related models. While “operational exhaust” arrived primarily as structured data, today’s corpus of data can include so-called unstructured data. Machine Learning Technology. Other Technologies. Conclusion.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

AWS Big Data

OCTOBER 18, 2023

Spark SQL is an Apache Spark module for structured data processing. FINRA centralizes all its data in Amazon Simple Storage Service (Amazon S3) with a remote Hive metastore on Amazon Relational Database Service (Amazon RDS) to manage their metadata information. or later installed.

Big Data 105

Big Data Data Processing Interactive Testing 105

AWS Big Data

FEBRUARY 22, 2023

An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data. The AWS Glue job can transform the raw data in Amazon S3 to Parquet format, which is optimized for analytic queries. All the metadata of the tables is stored in the AWS Glue Data Catalog, including the Hudi tables.

Data Lake 52

Data Lake Dashboards Cost-Benefit Data Warehouse 52

CIO Business Intelligence

DECEMBER 4, 2023

A modern information lifecycle management approach Today’s ILM approach recognizes the enterprise value of all digitized and enriched assets , avoiding the habituated, narrow reliance ontraditional structured data. Here is a high-level overview of the ILM steps and structure. Structure/Operationalize.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

Wayne Yaddow

MARCH 14, 2025

Data freshness propagation: No automatic tracking of data propagation delays across multiplemodels. Workaround: Implement custom metadata tracking scripts or use dbt Clouds freshness monitoring. Instead, they would need Apache Flink or Spark Structured Streaming.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52