AWS Big Data

FEBRUARY 29, 2024

First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses. Data enrichment In addition, additional metadata may need to be extracted from the objects.

Data Governance 102

Data Governance Unstructured Data Metadata Data Lake 102

CIO Business Intelligence

APRIL 25, 2024

“The challenge that a lot of our customers have is that requires you to copy that data, store it in Salesforce; you have to create a place to store it; you have to create an object or field in which to store it; and then you have to maintain that pipeline of data synchronization and make sure that data is updated,” Carlson said.

Data Integration 119

Data Integration Data Lake Data Warehouse Metadata 119

erwin

JUNE 26, 2020

The data catalog is a searchable asset that enables all data – including even formerly siloed tribal knowledge – to be cataloged and more quickly exposed to users for analysis. Three Types of Metadata in a Data Catalog. Technical Metadata. Operational Metadata. for analysis and integration purposes).

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

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 94

Metadata Metrics Data-driven Contextual Data 94

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.

Statistics 81

Statistics Data Warehouse Metadata Data Lake 81

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 82

Analytics Metadata Snapshot Data-driven 82

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. In order to integrate structured data, enterprises need to implement the data fabric pattern.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

Ontotext

NOVEMBER 11, 2024

Knowledge graphs, while not as well-known as other data management offerings, are a proven dynamic and scalable solution for addressing enterprise data management requirements across several verticals. The RDF-star extension makes it easy to model provenance and other structured metadata.

Metadata 52

Metadata Knowledge Discovery Data Integration Management 52

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

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

AWS Big Data

NOVEMBER 14, 2024

AWS Glue – The AWS Glue Data Catalog is your persistent technical metadata store in the AWS Cloud. Each AWS account has one Data Catalog per AWS Region. Each Data Catalog is a highly scalable collection of tables organized into databases. Meters) GPS value Speed s 1.0 (km/h)

Data Lake 86

Data Lake Metadata Testing Data-driven 86

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

CIO Business Intelligence

NOVEMBER 27, 2024

Good data governance has always involved dealing with errors and inconsistencies in datasets, as well as indexing and classifying that structured data by removing duplicates, correcting typos, standardizing and validating the format and type of data, and augmenting incomplete information or detecting unusual and impossible variations in the data.

Enterprise 140

Enterprise Data Quality Modeling Structured Data 140

Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. This blog focuses on governing spreadsheets that contain data, information, and metadata, and must themselves be governed. Data catalogs and spreadsheets are related in many ways.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

AWS Big Data

SEPTEMBER 12, 2024

Now, evidence generation leads (medical affairs, HEOR, and RWE) can have a natural-language, conversational exchange and return a list of evidence activities with high relevance considering both structured data and the details of the studies from unstructured sources. Overview of solution The solution was designed in layers.

Unstructured Data 103

Unstructured Data Metadata Consulting Machine Learning 103

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

CIO Business Intelligence

FEBRUARY 20, 2024

Here, industrial knowledge graphs are going to prove vital by enabling manufacturers to combine structured and unstructured data from a wide range of operational and enterprise software systems to drive better decision-making, problem-solving and more advanced automation.”

Data Architecture 98

Data Architecture Unstructured Data Manufacturing IT 98

Octopai

FEBRUARY 8, 2020

While some businesses suffer from “data translation” issues, others are lacking in discovery methods and still do metadata discovery manually. Moreover, others need to trace data history, get its context to resolve an issue before it actually becomes an issue. The solution is a comprehensive automated metadata platform.

Metadata 90

Metadata Key Performance Indicator Unstructured Data Business Intelligence 90

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 98

Data Lake Statistics Broadcasting Optimization 98

CIO Business Intelligence

MARCH 21, 2022

The data that data scientists analyze draws from many sources, including structured, unstructured, or semi-structured data. The more high-quality data available to data scientists, the more parameters they can include in a given model, and the more data they will have on hand for training their models.

Unstructured Data 137

Unstructured Data Data Analytics Analytics Data Science 137

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 Data Quality 119

Ontotext

SEPTEMBER 15, 2020

The Data Fabric paradigm combines design principles and methodologies for building efficient, flexible and reliable data management ecosystems. Knowledge Graphs are the Warp and Weft of a Data Fabric. To implement any Data Fabric approach, it is essential to be able to understand the context of data.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

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

erwin

SEPTEMBER 10, 2020

Whether you need to drill down for a granular view of a particular data set or create a high-level summary to describe a particular system and the data it relies on, end-to-end data lineage must be documented and tracked, with an emphasis on the dynamics of data processing and movement as opposed to data structures.

Data Governance 131

Data Governance Key Performance Indicator Metadata Digital Transformation 131

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

Octopai

SEPTEMBER 21, 2020

A crucial part of every company’s business intelligence (BI) is its data dictionary. When you have a well-structured data dictionary, you provide BI teams with an easy way to track and manage metadata throughout the entire enterprise. A data dictionary provides information about and context for your company’s data.

Metadata 52

Metadata Enterprise Structured Data Business Intelligence 52

FineReport

FEBRUARY 5, 2020

Metadata management. Users can centrally manage metadata, including searching, extracting, processing, storing, sharing metadata, and publishing metadata externally. The metadata here is focused on the dimensions, indicators, hierarchies, measures and other data required for business analysis.

Metadata 98

Metadata Dashboards Informatics Visualization 98

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 85

Metadata Big Data Optimization Unstructured Data 85

Ontotext

JULY 29, 2021

KGs bring the Semantic Web paradigm to the enterprises, by introducing semantic metadata to drive data management and content management to new levels of efficiency and breaking silos to let them synergize with various forms of knowledge management. The RDF data model and the other standards in W3C’s Semantic Web stack (e.g.,

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

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

AWS Big Data

MARCH 7, 2023

Sources Data can be loaded from multiple sources, such as systems of record, data generated from applications, operational data stores, enterprise-wide reference data and metadata, data from vendors and partners, machine-generated data, social sources, and web sources.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

Alation

OCTOBER 21, 2021

That dirty data then corrupts analyses and forces mistakes. A frequent and periodic data cleansing strategy is. Lack of metadata. A lack of organization is another sign of a data swamp, typically driven by bad or incomplete metadata.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 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 92

Cost-Benefit Metadata Structured Data Metrics 92

Octopai

FEBRUARY 27, 2020

The business intelligence & analytics environment becomes further complex when you consider the multiple systems in place processing data (database (DWH), ETL, analysis, reporting) that are all likely housing different descriptions of the same data, creating ONE. Want to acquire better data insights? The Octopai Difference.

Metadata 52

Metadata Data Warehouse Reporting Software 52

Ontotext

JULY 13, 2023

Enterprises generate an enormous amount of data and content every minute. Knowledge graphs allow organizations to enrich it with semantic metadata, making it ready to be used across teams and enterprise systems. Partner with PoolParty and GraphDB to build knowledge graphs for enterprise applications.

Enterprise 52

Enterprise Metadata Digital Transformation Software 52

Alation

JULY 19, 2022

A data catalog can assist directly with every step, but model development. And even then, information from the data catalog can be transferred to a model connector , allowing data scientists to benefit from curated metadata within those platforms. How Data Catalogs Help Data Scientists Ask Better Questions.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Ontotext

JANUARY 6, 2021

That means removing errors, filling in missing information and harmonizing the various data sources so that there is consistency. Once that is done, data can be transformed and enriched with metadata to facilitate analysis. Knowledge graphs help with data analysis in a number of ways.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59