AWS Big Data

MARCH 13, 2024

Data analytics – Business analysts gather operational insights from multiple data sources, including the location data collected from the vehicles. Athena is used to run geospatial queries on the location data stored in the S3 buckets. Choose Run.

Analytics 103

Analytics IoT Metadata Internet of Things 103

O'Reilly on Data

MARCH 31, 2020

You might have millions of short videos , with user ratings and limited metadata about the creators or content. Job postings have a much shorter relevant lifetime than movies, so content-based features and metadata about the company, skills, and education requirements will be more important in this case.

Management 332

Management Machine Learning Experimentation Metrics 332

CIO Business Intelligence

MARCH 29, 2022

Lowering the entry cost by re-using data and infrastructure already in place for other projects makes trying many different approaches feasible. Fortunately, learning-based projects typically use data collected for other purposes. . You have data but don’t use it. Why does valuable data so often go unused?

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

IBM Big Data Hub

FEBRUARY 14, 2024

The IBM team is even using generative AI to create synthetic data to build more robust and trustworthy AI models and to stand in for real-world data protected by privacy and copyright laws. These systems can evaluate vast amounts of data to uncover trends and patterns, and to make decisions.

Cost-Benefit 87

Cost-Benefit Insurance Unstructured Data Machine Learning 87

Alation

APRIL 25, 2023

More specifically, it describes the process of creating, administering, and adapting a comprehensive plan for how an organization’s data will be managed. In this way, data governance has implications for a wide range of data management disciplines, including data architecture, quality, security, metadata, and more.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

Alation

APRIL 25, 2023

More specifically, it describes the process of creating, administering, and adapting a comprehensive plan for how an organization’s data will be managed. In this way, data governance has implications for a wide range of data management disciplines, including data architecture, quality, security, metadata, and more.

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

Alation

JULY 7, 2022

In 2013 I joined American Family Insurance as a metadata analyst. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice. The use cases for metadata are boundless, offering opportunities for innovation in every sector.

Metadata 52

Metadata Data-driven Insurance Statistics 52

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 74

Data Strategy Strategy Data Warehouse Prescriptive Analytics 74

AWS Big Data

FEBRUARY 1, 2024

The Common Crawl corpus contains petabytes of data, regularly collected since 2008, and contains raw webpage data, metadata extracts, and text extracts. In addition to determining which dataset should be used, cleansing and processing the data to the fine-tuning’s specific need is required.

Metadata 105

Metadata Modeling Data Processing Unstructured Data 105

Cloudera

AUGUST 4, 2021

And if data security tops IT concerns, data governance should be their second priority. Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics.

Data Governance 83

Data Governance Metadata Data-driven Enterprise 83

Cloudera

DECEMBER 16, 2022

We’re proud to be recognized for the data management and data analytics innovations we have delivered in the new Cloudera Data Platform (CDP). Cloudera has always been in the forefront of disruptive technical innovation in data platforms. 4-Ready for modern data fabric architectures.

Management 88

Management Metadata Machine Learning Data Lake 88

AWS Big Data

FEBRUARY 21, 2023

It is a data modeling methodology designed for large-scale data warehouse platforms. What is a data vault? The data vault approach is a method and architectural framework for providing a business with data analytics services to support business intelligence, data warehousing, analytics, and data science needs.

Data Warehouse 67

Data Warehouse Data Lake Cost-Benefit Modeling 67

Domino Data Lab

OCTOBER 9, 2019

We’ll examine National Oceanic and Atmospheric Administration (NOAA) data management practices which I learned about at their workshop, as a case study in how to handle data collection, dataset stewardship, quality control, analytics, and accountability when the stakes are especially high. Metadata Challenges.

Deep Learning 69

Deep Learning Metadata Machine Learning Data Science 69

Andrew White

JANUARY 9, 2022

To drive a successful Data Analytics strategy do you think it is a multidisciplinary activity and if so, what additional roles would you expect to see involved. Have a look at this and see if this helps: Data, Analytics and AI Form the Foundation of Data-Driven Decision Making. . We write about data and analytics.

Analytics 64

Analytics Measurement Modeling Data-driven 64

datapine

JANUARY 31, 2022

Using business intelligence and analytics effectively is the crucial difference between companies that succeed and companies that fail in the modern environment. As the first and most impactful of all benefits of analytics, we have the ability to make informed strategic decisions backed by factual information.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 63

Data Architecture Data Lake Machine Learning Data Governance 63

DataKitchen

JANUARY 23, 2023

To capture a more complete picture of the data’s journey, it is important to have a DataOps Observability system in place. Data lineage is static and often lags by weeks or months. Data lineage is often considered static because it is typically based on snapshots of data and metadata taken at a specific time.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Alation

AUGUST 2, 2022

Too often, companies manage data in spreadsheets or individual databases. This means that you’re likely missing valuable insights that could be gleaned from data lakes and data analytics. Customer Data Privacy And Security. Data analyst onboarding time was reduced by 83%, from 1 year to 2 months.

Strategy 52

Strategy Cost-Benefit Metrics Data Lake 52

Andrew White

MARCH 31, 2023

See Product Management Practices Crucial for Data and Analytics Asset Monetization. Data mesh versus data fabric I am not the expert here but in lay terms, I believe both fabric and mesh include a semantic inference engine that consumes active metadata. Both build semantic maps that span silos of data.

Analytics 40

Analytics Marketing Visualization Data-driven 40

Jet Global

MAY 1, 2023

Use the experts in analytics to add value to your product. Let’s just give our customers access to the data. You’ve settled for becoming a data collection tool rather than adding value to your product. Four Approaches to Data Analytics The world of data analytics is constantly and quickly changing.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52