IBM Big Data Hub

FEBRUARY 14, 2024

Creative AI use cases Create with generative AI Generative AI tools such as ChatGPT, Bard and DeepAI rely on limited memory AI capabilities to predict the next word, phrase or visual element within the content it’s generating. Generative AI can produce high-quality text, images and other content based on the data used for training.

Cost-Benefit 89

Cost-Benefit Insurance Unstructured Data Machine Learning 89

Insight

MARCH 12, 2020

In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Data Collection The AIgent leverages book synopses and book metadata. The latter is any type of external data that has been attached to a book?—?for features) and metadata (i.e.

Modeling 59

Modeling Metadata Publishing Sales 59

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 97

Analytics IoT Metadata Internet of Things 97

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 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. They can use their own toolsets or rely on provided blueprints to ingest the data from source systems.

Dashboards 97

Dashboards Analytics Metadata Data Warehouse 97

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. of BI pages.

Metadata 98

Metadata Dashboards Informatics Visualization 98

IBM Big Data Hub

MARCH 29, 2024

Benefits of OpenTelemetry The OpenTelemetry protocol (OTLP) simplifies observability by collecting telemetry data, like metrics, logs and traces, without changing code or metadata. Prometheus metrics provide data points that consist of the metric name, label, timestamp and value by using a query language called PromQL.

Metrics 85

Metrics Visualization Measurement Optimization 85

AWS Big Data

AUGUST 23, 2023

It uses Amazon Simple Storage Service (Amazon S3) as the primary data storage for indexes, adding durability for your data. Collections are able to take advantage of the S3 storage layer to reduce the need for hot storage, and reduce cost, by bringing data into local store when it’s accessed. in OpenSearch Service).

Snapshot 94

Snapshot Dashboards Visualization Metrics 94

Cloudera

FEBRUARY 8, 2021

To accomplish this, ECC is leveraging the Cloudera Data Platform (CDP) to predict events and to have a top-down view of the car’s manufacturing process within its factories located across the globe. . Having completed the Data Collection step in the previous blog, ECC’s next step in the data lifecycle is Data Enrichment.

Manufacturing 118

Manufacturing Data Warehouse Sales Predictive Analytics 118

Alation

FEBRUARY 20, 2020

More than any other advancement in analytic systems over the last 10 years, Hadoop has disrupted data ecosystems. By dramatically lowering the cost of storing data for analysis, it ushered in an era of massive data collection. Disruptive Trend #2: Self-Service Analytics.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

Ontotext

MAY 18, 2020

These tools will allow them to effectively and efficiently handle extremely large volumes of disparate data – digitized histopathology slides from the visual and textual content of patient’s records, medical publications, diagnoses, etc. There are four types of data sources that the team will work with. Certainly not!

Knowledge Discovery 72

Knowledge Discovery Experimentation Data-driven Metadata 72

Domino Data Lab

JANUARY 21, 2021

While these tools are extremely useful for creating polished, reusable, visual dashboards for presenting data-driven insights, they are far less flexible in their ability to produce the information required to form the basis of a predictive modeling task. Data visualization blog posts are a dime a dozen. ref: [link].

Statistics 106

Statistics Unstructured Data Data Science Predictive Modeling 106

Alation

JANUARY 17, 2023

Data would be pulled from various sources, organized into, say, a table, and loaded into a data warehouse for mass consumption. This was not only time-consuming, but the growing popularity of cloud data warehouses compelled people to rethink this process. 2) Get a data ingestion tool and connect your data sources.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

Cloudera

JANUARY 21, 2021

With CDW, as an integrated service of CDP, your line of business gets immediate resources needed for faster application launches and expedited data access, all while protecting the company’s multi-year investment in centralized data management, security, and governance. Your data warehouse is ready.

Data Lake 95

Data Lake Data Warehouse IT Analytics 95

CIO Business Intelligence

SEPTEMBER 22, 2023

How to choose which DMP is right for your organization While each organization will have its own unique needs, a number of common factors are important to keep in mind when selecting a data management platform. The platform’s data collection, storage, scalability, and processing capabilities will also weigh heavily in making your choice.

Management 106

Management Advertising Data Lake Sales 106

Domino Data Lab

JULY 22, 2019

He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

CIO Business Intelligence

JUNE 9, 2022

Advertisers use OnAudience to build an understanding of their audience from data collected from multiple sources. The Data Management tool from SAS is designed to be heavily integrated with many data sources, be they data lakes, data pipes such as Hadoop, data fabrics, or mere databases. OnAudience.

Management 144

Management Advertising Data Lake Sales 144

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

datapine

JANUARY 31, 2022

BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions. BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. 6) Smart and faster reporting. click to enlarge**.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Rocket-Powered Data Science

MARCH 20, 2023

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. As you would guess, maintaining context relies on metadata.

Data Warehouse 324

Data Warehouse Metadata Digital Transformation Unstructured Data 324

Alation

FEBRUARY 17, 2023

Reichental describes data governance as the overarching layer that empowers people to manage data well ; as such, it is focused on roles & responsibilities, policies, definitions, metrics, and the lifecycle of the data. In this way, data governance is the business or process side. Here’s an example.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.” Yet finding data is just the beginning.

Metadata 64

Metadata Data Governance Dashboards Software 64

Cloudera

NOVEMBER 22, 2021

Explosion of data availability from a variety of sources, including on-premises data stores used by enterprise data warehousing / data lake platforms, data on cloud object stores typically produced by heterogenous, cloud-only processing technologies, or data produced by SaaS applications that have now evolved into distinct platform ecosystems (e.g.,

Data Processing 94

Data Processing Data Warehouse Enterprise Visualization 94

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

Sisense

MAY 18, 2020

AM: How is data collected to make these recommendations? YL: We’re interested in metadata. Yael Lev was a featured speaker in our webinar, “Humanizing BI Through Natural Language Processing and Knowledge Graphs,” alongside data scientist Ayelet Arditi and Sisense product marketing manager Julie Zuckerman.

Analytics 98

Analytics Digital Transformation Data-driven Sales 98

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

This is in contrast to traditional BI, which extracts insight from data outside of the app. We rely on increasingly mobile technology to comb through massive amounts of data and solve high-value problems. Plus, there is an expectation that tools be visually appealing to boot. Their dashboards were visually stunning.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52