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

Cloudera

FEBRUARY 16, 2022

We can think of model lineage as the specific combination of data and transformations on that data that create a model. This maps to the data collection, data engineering, model tuning and model training stages of the data science lifecycle. So, we have workspaces, projects and sessions in that order.

Machine Learning 89

Machine Learning Modeling Metadata Recreation/Entertainment 89

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

IBM Big Data Hub

MARCH 29, 2024

OpenTelemetry and Prometheus enable the collection and transformation of metrics, which allows DevOps and IT teams to generate and act on performance insights. OTel was born from the merger of OpenCensus and OpenTracing with the goal of providing APIs, SDKs, libraries and integrations that standardize the collection of disparate data.

Metrics 75

Metrics Visualization Measurement Optimization 75

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. Data providers and consumers are the two fundamental users of a CDH dataset.

Dashboards 104

Dashboards Analytics Metadata Data Warehouse 104

AWS Big Data

MARCH 26, 2024

The following figure shows some of the metrics derived from the study. 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. Then, you transform this data into a concise format.

Data Strategy 76

Data Strategy Strategy Data Warehouse Prescriptive Analytics 76

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.

Snapshot 97

Snapshot Dashboards Visualization Metrics 97

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.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

Cloudera

JUNE 6, 2019

While this approach provides isolation, it creates another significant challenge: duplication of data, metadata, and security policies, or ‘split-brain’ data lake. Now the admins need to synchronize multiple copies of the data and metadata and ensure that users across the many clusters are not viewing stale information.

Metadata 89

Metadata Data Lake Optimization Strategy 89

Alation

OCTOBER 12, 2022

It is important to take into account that not all numeric data can be part of a calculation or aggregated. These terms that cannot aggregate, like a percentage, are often called non-aggregatable metrics. What Is Quantitative Data Analysis? What Are Quantitative Data Collection Methods?

Statistics 52

Statistics Sales Testing Marketing 52

Juice Analytics

FEBRUARY 21, 2018

This means that two different rows in the data can represent the same entity with data collected for it at different points in time. As a consequence of the rule above, the data should include a row identifier column that can be repeated to indicate that different rows of data are representing the same entities.

Metadata 53

Metadata Metrics Data Collection Reporting 53

AWS Big Data

FEBRUARY 21, 2023

Regardless of the division or use case it is related to, dimensional data models can be used to store data obtained from tracking various processes like patient encounters, provider practice metrics, aftercare surveys, and more. It enables concurrent data loading and eliminates the need for a corporate vault.

Data Warehouse 70

Data Warehouse Data Lake Cost-Benefit Metadata 70

Alation

FEBRUARY 8, 2022

Middlemen — data engineering or IT teams — can’t possibly possess all the expertise needed to serve up quality data to the growing range of data consumers who need it. As data collection has surged, and demands for data have grown in the enterprise, one single team can no longer meet the data demands of every department.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 52

Domino Data Lab

JULY 22, 2019

You know, typically, when you think about running projects, running teams, in terms of setting the priorities for projects, in terms of describing, what are the key metrics for success for a project, that usually falls on product management. How can you trace that all the way back into the data collection?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Andrew White

JANUARY 9, 2022

This is the same for scope, outcomes/metrics, practices, organization/roles, and technology. Check this out: The Foundation of an Effective Data and Analytics Operating Model — Presentation Materials. Where these efforts break down is in the data that goes into the connection at one end and comes out the other.

Analytics 64

Analytics Measurement Data-driven Modeling 64

DataKitchen

JUNE 24, 2021

GE formed its Digital League to create a data culture. One of the keys for our success was really focusing that effort on what our key business initiatives were and what sorts of metrics mattered most to our customers. Chapin also mentioned that measuring cycle time and benchmarking metrics upfront was absolutely critical. “It

ROI 211

ROI Metrics Measurement Cost-Benefit 211

datapine

JANUARY 31, 2022

They used the data collected to build a logistic-regression and unsupervised learning models, so as to determine the potential relationship between drivers and outcomes. Overall, the use of data analysis in this use case showed a significant increase in employee collaboration and increased operational efficiency for the company.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Alation

NOVEMBER 11, 2021

Let’s take a look at some of the key principles for governing your data in the cloud: What is Cloud Data Governance? Cloud data governance is a set of policies, rules, and processes that streamline data collection, storage, and use within the cloud. This framework maintains compliance and democratizes data.

Data Governance 52

Data Governance Data Quality Metrics Metadata 52

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

JULY 6, 2021

But first, they need to understand the top challenges to data governance, unique to their organization. Source: Gartner : Adaptive Data and Analytics Governance to Achieve Digital Business Success. As data collection and volume surges, so too does the need for data strategy. Why Do Data Silos Happen?

Data Governance 52

Data Governance Metadata Data Quality Risk 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

Alation

AUGUST 2, 2022

Establishing and monitoring metrics that validate improvements. Using Alation’s curated data catalog , the company’s California-based data analysts efficiently collaborated with their peers in the Philippines to optimize their analysis efforts. Data analyst onboarding time was reduced by 83%, from 1 year to 2 months.

Metrics 52

Metrics Cost-Benefit Strategy Data Lake 52

DataKitchen

JANUARY 23, 2023

On the other hand, DataOps Observability refers to understanding the state and behavior of data as it flows through systems. It allows organizations to see how data is being used, where it is coming from, and how it is being transformed. Data lineage is static and often lags by weeks or months.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Jet Global

MAY 1, 2023

As a result, end users can better view shared metrics (backed by accurate data), which ultimately drives performance. 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. Let them do what they want outside of the application.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52