Smart Data Collective

JULY 1, 2023

Image annotation is the act of labeling images for AI and machine learning models. This helps train the AI model by assigning classes to different entities in an image. The resulting structured data is then used to train a machine learning algorithm. Consistency and agreement Establish an agreement metric (e.g.,

Metrics 64

Metrics Machine Learning Uncertainty Deep Learning 64

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 133

Unstructured Data Data Analytics Analytics Structured Data 133

O'Reilly on Data

APRIL 19, 2021

Relatively few respondents are using version control for data and models. Tools for versioning data and models are still immature, but they’re critical for making AI results reproducible and reliable. This makes sense, given that we don’t see heavy usage of tools for model and data versioning. form data).

Enterprise 353

Enterprise Modeling Risk Manufacturing 353

IBM Big Data Hub

NOVEMBER 29, 2023

Furthermore, AI algorithms’ capacity for recognizing patterns—by learning from your company’s unique historical data—can empower businesses to predict new trends and spot anomalies sooner and with low latency. Stream analytics can be used to help improve the speed and accuracy of models’ predictions.

Unstructured Data 86

Unstructured Data Data-driven ROI Machine Learning 86

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

Data Lake 92

Data Lake Unstructured Data Management Modeling 92

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 78

Data Science Data Analytics Prescriptive Analytics Analytics 78

CIO Business Intelligence

DECEMBER 4, 2023

Once focused solely on reducing search and retrieval times, information lifecycle management (ILM) is now critical to workflow automation, identifying and tracking performance metrics, and harnessing the burgeoning potential of AI. Operationalizing data to drive revenue CIOs report that their roles are rising in importance and impact.

Unstructured Data 52

Unstructured Data Data Lake Metadata Business Objectives 52

AWS Big Data

MARCH 2, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to use SQL for analyzing structured and semi-structured data with best price performance along with secure access to the data. This could be a user, role, or group. Privilege – The type of operation.

Visualization 81

Visualization Dashboards Data Warehouse Metrics 81

AWS Big Data

MARCH 27, 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. Complete the implementation tasks such as data ingestion and performance testing.

Testing 101

Testing Data Warehouse Metrics Cost-Benefit 101

Ontotext

OCTOBER 14, 2021

For the purposes of this article, you just need to know the following: A graph is a method of storing and modeling data that uniquely captures the relationships between data. These nodes include metrics and attributes extracted from structured data sources as well as qualitative data stored in unstructured documents.

Reporting 98

Reporting Structured Data Metadata Data Warehouse 98

Ontotext

JUNE 22, 2023

All derived facts can be further put into context with structured data, which improves data quality and presents researchers with clear evidence and provenance for all insights Then, Ontotext’s Target Discovery provides deeper insights into the data stored in this highly-interlinked knowledge graph, where long sequences of relations can be mined.

Metrics 52

Metrics Statistics Visualization Metadata 52

Alation

FEBRUARY 20, 2020

Architecturally the introduction of Hadoop, a file system designed to store massive amounts of data, radically affected the cost model of data. Organizationally the innovation of self-service analytics, pioneered by Tableau and Qlik, fundamentally transformed the user model for data analysis.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

CIO Business Intelligence

JUNE 14, 2023

In the case of intelligent operations, real-time data informs immediate operational decisions. An airline carrier needs to know how many gates are open and how many passengers are on each plane – metrics that change from moment to moment. Consider data types.

Unstructured Data 62

Unstructured Data IT Manufacturing Visualization 62

AWS Big Data

MARCH 26, 2024

The following figure shows some of the metrics derived from the study. Unified customer profile Graph databases excel in modeling customer interactions and relationships, offering a comprehensive view of the customer journey. Data warehouses can provide a unified, consistent view of a vast amount of customer data for C360 use cases.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

AWS Big Data

MARCH 7, 2023

You can use simple SQL to analyze structured and semi-structured data across data warehouses, data marts, operational databases, and data lakes to deliver the best price performance at any scale. Data in Amazon S3 can be easily queried in place using SQL with Amazon Redshift Spectrum.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74

AWS Big Data

JULY 12, 2023

With a wide array of data sources, including transactional databases, log files, and event streams, you need a simple-to-use solution capable of efficiently ingesting and transforming large volumes of data in real time, ensuring data cleanliness, structural integrity, and data team collaboration.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

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

IBM Big Data Hub

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data.

Data mining 54

Data mining Machine Learning Deep Learning Marketing 54

FineReport

MARCH 7, 2024

Data Acquisition I categorize data sources into three types: (1) First-party data: User factual data, such as financial products purchased at a certain institution, time of purchase, issuing branch, name, phone number, or operational data, such as user behavioral data on a financial app. (2)

Dashboards 52

Dashboards Reporting Advertising Statistics 52

Sisense

JUNE 8, 2020

“The cloud data platform enables a data marketplace where organizations can obtain secure and governed consumer and government data, such as COVID-19 data, to make timely decisions in challenging times.”. In short, cloud data warehouses and BI platforms have revolutionized the way organizations share and use data.

Data Warehouse 89

Data Warehouse Data-driven Dashboards Sales 89

AWS Big Data

JANUARY 22, 2024

The success of the implementation meant assessing various aspects of the data infrastructure, data management, and business outcomes. 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.

Data-driven 87

Data-driven Advertising Metadata Data Architecture 87

Jet Global

MAY 9, 2024

Machine Learning Pipelines : These pipelines support the entire lifecycle of a machine learning model, including data ingestion , data preprocessing, model training, evaluation, and deployment. API Data Pipelines : These pipelines retrieve data from various APIs and load it into a database or application for further use.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Domino Data Lab

MARCH 3, 2019

What’s been the impact of using ML models on culture and organization? Who builds their models? What metrics are used to evaluate success? We also used maturity , in other words how long had an enterprise organization been deploying ML models in production?

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

AWS Big Data

NOVEMBER 9, 2023

Data sources As part of this data platform, we are ingesting data from diverse and varied data sources, including: Transactional databases – These are active databases that store real-time data from various applications. Third-party APIs – These provide analytics and survey data related to ecommerce websites.

Data Warehouse 107

Data Warehouse Testing Data Quality Reporting 107

Alation

OCTOBER 28, 2021

Healthcare is changing, and it all comes down to data. Leaders in healthcare seek to improve patient outcomes, meet changing business models (including value-based care ), and ensure compliance while creating better experiences. Data & analytics represents a major opportunity to tackle these challenges.

Data Governance 52

Data Governance Measurement Metrics Modeling 52

AWS Big Data

DECEMBER 21, 2023

For the downstream consumption by all departments across the organization, smava’s Data Platform team prepares curated data products following the extract, load, and transform (ELT) pattern. The Raw Vault describes objects loaded directly from the data sources and represents a copy of the landing stage in the data lake.

Data Lake 91

Data Lake Data Warehouse Data-driven B2B 91

AWS Big Data

APRIL 19, 2023

Different departments within an organization can place data in a data lake or within their data warehouse depending on the type of data and usage patterns of that department. This keeps data engineering costs low and expands analytics for more users. About the authors Sana Ahmed is a Sr.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Cloudera

JANUARY 11, 2018

Cloudera often partners with these companies to define the desired path, set reasonable milestones and success metrics, and aide solution design. “Bringing together as much of this data and information as possible will help organizations gain a richer, more detailed picture of customers. . ” And teases at the reward.

Strategy 40

Strategy Data Warehouse Cost-Benefit Marketing 40