O'Reilly on Data

DECEMBER 19, 2018

If you suddenly see unexpected patterns in your social data, that may mean adversaries are attempting to poison your data sources. Anomaly detection may have originated in finance, but it is becoming a part of every data scientist’s toolkit. Tim Kraska on “How machine learning will accelerate data management systems”.

Machine Learning 279

Machine Learning Software Metadata Testing 279

AWS Big Data

OCTOBER 25, 2023

Most companies produce and consume unstructured data such as documents, emails, web pages, engagement center phone calls, and social media. 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.

Unstructured Data 133

Unstructured Data Metadata Management Analytics 133

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

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

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

AWS Big Data

OCTOBER 2, 2023

For a deeper exploration on configuring and using streaming ingestion in Amazon Redshift , refer to Real-time analytics with Amazon Redshift streaming ingestion. For streams that contain the raw binary data encoded in JSON format, Amazon Redshift provides a variety of tools for parsing and managing the data.

Cost-Benefit 115

Cost-Benefit Metadata Structured Data Data-driven 115

AWS Big Data

AUGUST 15, 2024

Data producers (data owners) can add context and control access through predefined approvals, providing secure and governed data sharing. To learn more about the core components of Amazon DataZone, refer to Amazon DataZone terminology and concepts.

Data Quality 111

Data Quality Visualization Metadata Key Performance Indicator 111

FineReport

FEBRUARY 5, 2020

Based on the study of the evaluation criteria of Gartner Magic Quadrant for analytics and Business Intelligence Platforms, I have summarized top 10 key features of BI tools for your reference. Overall, as users’ data sources become more extensive, their preferences for BI are changing. Metadata management. Analytics dashboards.

Metadata 98

Metadata Dashboards Informatics Visualization 98

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 111

Metadata Metrics Data-driven Contextual Data 111

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 97

Analytics Data Warehouse Data Lake Metadata 97

Rocket-Powered Data Science

JULY 19, 2023

The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage. A similarly high percentage of tabular data usage among data scientists was mentioned here.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

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 116

Data Lake Statistics Broadcasting Optimization 116

AWS Big Data

JULY 28, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. It is designed for analyzing large volumes of data and performing complex queries on structured and semi-structured data. Tags provide metadata about resources at a glance.

Snapshot 98

Snapshot Metadata Measurement Data Warehouse 98

AWS Big Data

AUGUST 15, 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. Similarly, individual business units produce their own domain-specific data. In this post, we use three AWS accounts.

Data Lake 122

Data Lake Data Warehouse Data Governance Publishing 122

erwin

AUGUST 31, 2023

Let’s explore the continued relevance of data modeling and its journey through history, challenges faced, adaptations made, and its pivotal role in the new age of data platforms, AI, and democratized data access. Embracing the future In the dynamic world of data, data modeling remains an indispensable tool.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 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 87

Metadata Big Data Optimization Machine Learning 87

AWS Big Data

JUNE 26, 2024

If you’re new to Amazon DataZone, refer to Getting started. Use case 1: Bring your own role and resources Customers manage data platforms that consist of AWS managed services such as AWS Lake Formation , Amazon S3 for data lakes, AWS Glue for ETL, and so on. Otherwise, refer to Create domains for instructions to set up a domain.

Data Lake 119

Data Lake Data Warehouse Unstructured Data Data Governance 119

Ontotext

MAY 26, 2021

Without all this background knowledge, before computers can perform like humans, they need a machine-readable point of reference that represents “the ground truth”. One of the main uses of the Gold Standard is to train AI systems to identify the patterns in various types of data with the help of machine learning (ML) algorithms.

Data Quality 87

Data Quality Machine Learning Measurement Metadata 87

AWS Big Data

AUGUST 5, 2024

These business units have varying landscapes, where a data lake is managed by Amazon Simple Storage Service (Amazon S3) and analytics workloads are run on Amazon Redshift , 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.

Data Lake 105

Data Lake Finance Sales Management 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. In order to integrate structured data, enterprises need to implement the data fabric pattern.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

BizAcuity

MARCH 29, 2019

Load data into staging, perform data quality checks, clean and enrich it, steward it, and run reports on it completing the full management cycle. Numbers are only good if the data quality is good. To get an in-depth knowledge of the practices mentioned above please refer to the blog on Oracle’s webpage.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

AWS Big Data

NOVEMBER 22, 2023

Data lakes are designed for storing vast amounts of raw, unstructured, or semi-structured data at a low cost, and organizations share those datasets across multiple departments and teams. The queries on these large datasets read vast amounts of data and can perform complex join operations on multiple datasets.

Statistics 131

Statistics Data Lake Optimization Data-driven 131

AWS Big Data

MARCH 25, 2024

To learn more about RAG, refer to Question answering using Retrieval Augmented Generation with foundation models in Amazon SageMaker JumpStart. A RAG-based generative AI application can only produce generic responses based on its training data and the relevant documents in the knowledge base.

Data Lake 122

Data Lake Unstructured Data Management Snapshot 122

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

AWS Big Data

JANUARY 22, 2024

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. In this approach, teams responsible for generating data are referred to as producers.

Data-driven 118

Data-driven Advertising Metadata Data Architecture 118

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

AWS Big Data

MARCH 26, 2024

Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history. Then, you transform this data into a concise format. The following screenshot shows an example C360 dashboard built on QuickSight.

Data Strategy 103

Data Strategy Strategy Data Warehouse Prescriptive Analytics 103

AWS Big Data

MARCH 13, 2024

AWS Glue crawls both S3 bucket paths, populates the AWS Glue database tables based on the inferred schemas, and makes the data available to other analytics applications through the AWS Glue Data Catalog. Athena is used to run geospatial queries on the location data stored in the S3 buckets. Choose Run.

Analytics 122

Analytics IoT Metadata Internet of Things 122

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

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

Ontotext

OCTOBER 12, 2023

“[LLMs] call into question a fundamental tenet of Data Management: that in order to address non-trivial information needs, the first step is to explicitly structure data in order to lift them from the ambiguous swamp of our human language.

Modeling 75

Modeling Recreation/Entertainment Data Processing Metadata 75

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

MAY 18, 2020

Exascale computing refers to systems capable of at least one exaFLOPS calculation per second and that is billion billion (or if you wish a quintillion) operations per second. Behind the scenes of linking histopathology data and building a knowledge graph out of it. There are four types of data sources that the team will work with.

Knowledge Discovery 72

Knowledge Discovery Experimentation Data-driven Metadata 72

Ontotext

FEBRUARY 26, 2024

RED’s focus on news content serves a pivotal function: identifying, extracting, and structuring data on events, parties involved, and subsequent impacts. A risk and opportunity event refers to an occurrence that may positively or negatively impact the stock market performance of a company or industry sector.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

Ontotext

JULY 6, 2023

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. There are four groups of data that are naturally siloed: Structured data (e.g.,

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52