O'Reilly on Data

JULY 28, 2020

If this sounds fanciful, it’s not hard to find AI systems that took inappropriate actions because they optimized a poorly thought-out metric. CTRs are easy to measure, but if you build a system designed to optimize these kinds of metrics, you might find that the system sacrifices actual usefulness and user satisfaction.

Marketing 362

Marketing Experimentation Metrics Testing 362

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 88

Cost-Benefit Insurance Unstructured Data Machine Learning 88

bridgei2i

MARCH 11, 2021

Creating an efficient data governance strategy means – Breaking down all sources of accumulated data across the organization. Recognizing the “right” data that can be optimized by AI-powered business analytics tools. Identify data errors and eliminate them from the system. in the system.

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 52

Octopai

OCTOBER 11, 2021

Unlike the rock collection or shell collection you may have had as a child, you don’t collect data in order to have a data collection. You collect data to use it. Data needs to be accompanied by the metadata that explains and gives it context.

Metadata 90

Metadata Data Collection Optimization IT 90

Ontotext

FEBRUARY 14, 2024

CEEL is now immediately available as part of our text analysis offerings, coming preconfigured as part of the new version of the Ontotext Metadata Studio (OMDS). This makes it an effective and cost-efficient system for extracting entities from large-scale data collections. This approach has certain benefits.

Cost-Benefit 52

Cost-Benefit Modeling Metadata Optimization 52

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. This method uses GZIP compression to optimize storage consumption and query performance. Choose Run.

Analytics 94

Analytics IoT Metadata Internet of Things 94

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 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

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

Alation

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? Do they have a system to manage the metadata for given assets? One example is the EU’s General Data Protection Regulation (GDPR).

Data Governance 52

Data Governance Strategy Data Quality Marketing 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 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

AWS Big Data

NOVEMBER 15, 2023

BMW Group uses 4,500 AWS Cloud accounts across the entire organization but is faced with the challenge of reducing unnecessary costs, optimizing spend, and having a central place to monitor costs. The ultimate goal is to raise awareness of cloud efficiency and optimize cloud utilization in a cost-effective and sustainable manner.

Dashboards 94

Dashboards Analytics Metadata Data Warehouse 94

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Online, offline or nonline.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

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 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

IBM Big Data Hub

MARCH 29, 2024

Monitoring and optimizing application performance is important for software developers and enterprises at large. The more applications that an enterprise deploys, the more data that exists for collecting and analyzing. Analyzing telemetry data is key in understanding system performance and health.

Metrics 83

Metrics Visualization Measurement Optimization 83

Cloudera

DECEMBER 16, 2022

Notably, these same services simplify repatriating data workloads back to private clouds, to save on cloud infrastructure expenses. Cloudera is closely partnered with the leading cloud service providers (CSPs), and has optimized our platform and services to run as efficiently on their infrastructure services as possible.

Management 88

Management Metadata Machine Learning Data Lake 88

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.

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

Ontotext

MAY 5, 2023

It is reused in modeling the publication of entity data or regulatory-mandated data exchange, as seen in the example provided below. Integrating reporting to move to a more streamlined, efficient approach to data collection. We think their adoption will bring benefits well beyond reporting.

Data Collection 64

Data Collection Risk Data-driven Interactive 64

FineReport

FEBRUARY 5, 2020

To put it bluntly, users increasingly want to do their own data analysis without having to find support from the IT department. Metadata management. Users can centrally manage metadata, including searching, extracting, processing, storing, sharing metadata, and publishing metadata externally. Analytics dashboards.

Metadata 98

Metadata Dashboards Informatics Visualization 98

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 85

Metadata Data Lake Optimization Strategy 85

Cloudera

AUGUST 4, 2021

Data governance used to be considered a “nice to have” function within an enterprise, but it didn’t receive serious attention until the sheer volume of business and personal data started taking off with the introduction of smartphones in the mid-2000s.

Data Governance 83

Data Governance Metadata Data-driven Enterprise 83

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 114

Manufacturing Data Warehouse Sales Predictive Analytics 114

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 93

Snapshot Dashboards Visualization Metrics 93

Alation

FEBRUARY 20, 2020

Not only can resources be quickly provisioned and optimized for different workloads and processing needs, but it can be done cost effectively. With an on-premise deployment, enterprises have full control over data security, data access, and data governance. In The Alation Data Catalog adding S3 is simple.

Data Lake 52

Data Lake ROI Metadata Cost-Benefit 52

AWS Big Data

FEBRUARY 21, 2023

We dive deep into a hybrid approach that aims to circumvent the issues posed by these two and also provide recommendations to take advantage of this approach for healthcare data warehouses using Amazon Redshift. What is a dimensional data model? It optimizes the database for faster data retrieval. What is a hybrid model?

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

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 101

Management Advertising Data Lake Sales 101

AWS Big Data

JULY 3, 2023

Backtesting is a process used in quantitative finance to evaluate trading strategies using historical data. This helps traders determine the potential profitability of a strategy and identify any risks associated with it, enabling them to optimize it for better performance.

Snapshot 82

Snapshot Data Lake Testing Strategy 82

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

The problems down in the mature bucket, those are optimizations, they aren’t showstoppers. We had Julia Lane talking about Coleridge Initiative and the work on Project Jupyter to support metadata and data governance and lineage. Machine learning is a subset of mathematical optimization.

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. What began as a relatively simple data management tool has grown to be a portal for tracking the performance of digital advertising across channels. OnAudience.

Management 139

Management Advertising Data Lake Sales 139

Andrew White

JANUARY 9, 2022

Where these efforts break down is in the data that goes into the connection at one end and comes out the other. So, I hear you say, let’s share metadata and make the data self-describing. I would think a key importance would be how you generate and what data points are used to analyze especially if it is manually retrieved.

Analytics 64

Analytics Measurement Modeling Data-driven 64

The Unofficial Google Data Science Blog

SEPTEMBER 9, 2015

Record-level program scope As a data scientist, you write a Sawzall script to operate at the level of a single record. The scope of each record is determined by the source of the data; it might be a web page, metadata about an app, or logs from a web server. However, it turns out to be quite useful for data science applications.

Data Science 56

Data Science Statistics Testing Metadata 56

datapine

JANUARY 31, 2022

As mentioned above, one of the great benefits of business intelligence and analytics is the ability to make informed data-based decisions. This benefit goes directly in hand with the fact that analytics provide businesses with technologies to spot trends and patterns that will lead to the optimization of resources and processes.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Alation

MARCH 17, 2021

According to the Forrester Wave: Machine Learning Data Catalogs, Q4 2020 , “Alation exploits machine learning at every opportunity to improve data management, governance, and consumption by analytic citizens. The automation of these processes supports the larger goal of data-driven decision making within the enterprise.

Machine Learning 52

Machine Learning Metadata Data Governance Interactive 52

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

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 64

Data Architecture Data Lake Machine Learning Data Governance 64

O'Reilly on Data

DECEMBER 19, 2018

We won’t be writing code to optimize scheduling in a manufacturing plant; we’ll be training ML algorithms to find optimum performance based on historical data. With machine learning, the challenge isn’t writing the code; the algorithms are implemented in a number of well-known and highly optimized libraries.

Machine Learning 261

Machine Learning Software Testing Metadata 261