DataRobot Blog

MARCH 10, 2022

As a result of these technological advancements, the manufacturing industry has set its sights on artificial intelligence and automation to enhance services through efficiency gains and lowering operational expenses. Manufacturers are attempting to monitor their facilities in near real-time. Factory Monitoring?—?

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Manufacturing IoT Machine Learning Forecasting 52

DataKitchen

MAY 10, 2021

Data operations is manufacturing. You run a factory and that factory produces insight in the form of data sets, dashboards, and other tools. The data factory transforms raw materials (source data) into finished goods (analytics) using a series of processing steps (Figure 1). It’s not about data quality .

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Testing Manufacturing Data Quality Statistics 214

CIO Business Intelligence

JANUARY 23, 2024

Efficiency metrics might show the impacts of automation and data-driven decision-making. For example, manufacturers should capture how predictive maintenance tied to IoT and machine learning saves money and reduces outages. For example, in media and ecommerce, CIOs may select revenue growth from digital subscriptions and advertising.

Measurement 134

Measurement Digital Transformation KPI Metrics 134

TDAN

MAY 17, 2022

One of the greatest contributions to the understanding of data quality and data quality management happened in the 1980s when Stuart Madnick and Rich Wang at MIT adapted the concept of Total Quality Management (TQM) from manufacturing to Information Systems reframing it as Total Data Quality Management (TDQM).

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Data Quality Manufacturing Management IT 52

Octopai

MAY 2, 2022

It may not sound like such a big difference, but that switch affects your users’ expectations – and, therefore, what makes your data analytics team a productivity and profitability success. . Let’s take a look at the average person’s expectations about paying for products: You order a car direct from the manufacturer.

Manufacturing 87

Manufacturing Testing Experimentation Data Quality 87

datapine

NOVEMBER 27, 2019

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM).

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

CIO Business Intelligence

MAY 21, 2024

Unlike many other events, which consist of multiple racing teams and manufacturers, Porsche Carrera Cup Brasil provides and maintains all 75 cars used in the race. One of the first things they needed was an IoT device that could be plugged into the cars to gather and transmit the data.

Broadcasting 107

Broadcasting Recreation/Entertainment Manufacturing Data Lake 107

IBM Big Data Hub

MAY 9, 2024

At the same time, implementing a data governance framework poses some challenges, such as data quality issues, data silos security and privacy concerns. Data quality issues Positive business decisions and outcomes rely on trustworthy, high-quality data.

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Data Governance Data Quality Insurance Predictive Analytics 69

CIO Business Intelligence

JUNE 1, 2022

The digital twins at McLaren are also used to run simulations for the design of new parts and then to test them for performance and reliability before they are manufactured and installed in the racing cars. Success stories abound in industries including manufacturing, utilities, life sciences, oil and gas, and research environments. .

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Manufacturing Digital Transformation Predictive Analytics Strategy 106

CIO Business Intelligence

NOVEMBER 7, 2023

Lexmark uses a data lakehouse architecture that it built on top of a Microsoft Azure environment. This has enabled every function to embrace data to make decisions, like which products to manufacture, how to price them, how much inventory to hold, and even predict when each device that we have deployed will break down,” Gupta says.

Data Warehouse 141

Data Warehouse Digital Transformation Data-driven Reporting 141

O'Reilly on Data

JUNE 18, 2019

As model building become easier, the problem of high-quality data becomes more evident than ever. Even with advances in building robust models, the reality is that noisy data and incomplete data remain the biggest hurdles to effective end-to-end solutions. Data integration and cleaning.

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Machine Learning Data Quality Statistics Modeling 255

IBM Big Data Hub

JANUARY 25, 2024

Many managers in asset-intensive industries like energy, utilities or process manufacturing, perform a delicate high-wire act when managing inventory. Generative AI has the potential to deliver powerful support in key data areas: Master data cleansing to reduce duplications and flag outliers. What’s at stake?

Optimization 76

Optimization Cost-Benefit Prescriptive Analytics Manufacturing 76

Rocket-Powered Data Science

MARCH 20, 2023

Datasphere is an enhanced data warehousing service that includes business semantics (through both analytic and relational models) and a knowledge graph (linking business content with business context).

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325

Octopai

AUGUST 8, 2023

As we continue to work with multiple clients, we see a consistent trend where organizations are struggling to improve their data quality and see that as one of the most common barriers to true value realization through digital transformation. Coupling our data experts, with this incredible solution, is a win-win for our clients.”

Digital Transformation 52

Digital Transformation Metadata Forecasting Data-driven 52

CIO Business Intelligence

DECEMBER 6, 2023

The relationship between the global aircraft manufacturer Airbus and FPT Software can epitomise this model. As a result, companies are more likely to look for tech partners that excel in IT services while being able to join hands to drive innovative strategies and future technologies.

Digital Transformation 113

Digital Transformation Software Cost-Benefit Manufacturing 113

CIO Business Intelligence

DECEMBER 22, 2022

DataOps teams also seek to orchestrate data, tools, code, and environments from beginning to end, with the aim of providing reproducible results. Such teams tend to view analytic pipelines as analogous to lean manufacturing lines and regularly reflect on feedback provided by customers, team members, and operational statistics.

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Analytics Machine Learning Software Data Quality 128

Smart Data Collective

OCTOBER 29, 2023

Simply by turning vast amounts of data into smart business decisions. Consider drug manufacturers for example, where big data acts as their hidden ally. Both patients and manufacturers reap the benefits here. What’s more is that it alleviates patient suffering during these trials.

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Management Big Data Manufacturing Data-driven 102

IBM Big Data Hub

MAY 15, 2024

Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges. Edge computing data processing Edge computing is becoming increasingly prevalent, especially in industries such as manufacturing, healthcare and IoT.

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Cost-Benefit Data Integration Data Architecture Manufacturing 70

Alation

SEPTEMBER 28, 2022

DataOps is essentially a mix of these methodologies: Lean manufacturing. However, some may confuse it as DevOps for data , but that’s not the case, as there are key differences between DevOps and DataOps. DataOps strategies share these common elements: Collaboration among data professionals and business stakeholders.

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

CIO Business Intelligence

JANUARY 30, 2024

Birgit Fridrich, who joined Allianz as sustainability manager responsible for ESG reporting in late 2022, spends many hours validating data in the company’s Microsoft Sustainability Manager tool. Data quality is key, but if we’re doing it manually there’s the potential for mistakes.

Reporting 105

Reporting Data Quality Strategy Data-driven 105

Smarten

DECEMBER 3, 2023

‘Giving your team the right tools and a simple way to manage the overwhelming flow of data is crucial to business success.’ FreeCodeCamp reports success in augmented analytics across many industries and business functions, including Retail, Manufacturing, Healthcare, and Financial Services. So, what does all this mean to your business?

Analytics 40

Analytics Cost-Benefit Data Quality Consulting 40

Cloudera

JULY 20, 2021

Most businesses, whether you are in Retail, Manufacturing, Specialty Chemicals, Telecommunications, consider a 10% market capitalization increase from 2020 to 2021 outstanding. But what would you say to your shareholders when they found out your competitors’ market capitalization grew 35%?

Manufacturing 104

Manufacturing Forecasting IoT Insurance 104

O'Reilly on Data

APRIL 19, 2021

The biggest problems in this year’s survey are lack of skilled people and difficulty in hiring (19%) and data quality (18%). The biggest skills gaps were ML modelers and data scientists (52%), understanding business use cases (49%), and data engineering (42%). Bad data yields bad results at scale.

Enterprise 353

Enterprise Modeling Risk Manufacturing 353

Ontotext

MAY 22, 2023

Master data management (MDM), on the other hand, is focused on ensuring data quality and consistency across different systems and applications. MDM creates a single, verified source of data that can be used throughout an organization, and enforce policies and standards to maintain data quality.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

Smarten

APRIL 19, 2024

The value of an AI-focused analytics solution can only be fully realized when a business has ensured data quality and integration of data sources, so it will be important for businesses to choose an analytics solution and service provider that can help them achieve these goals.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

CIO Business Intelligence

MAY 24, 2023

If the data is correctly curated and formatted, it can be used by data analytics and, in particular, AI to make recommendations that help an organization make decisions ahead of the market. Poor data quality leads to poor decisions and recommendations. Without frameworks, people tend to protect their data,” she says.

Data Governance 102

Data Governance Data Quality Data Collection Manufacturing 102

DataKitchen

MARCH 16, 2023

Under Efficiency, the Number of Data Product Owners metric measures the value of the business’s data products. Under Quality, the Data Quality Incidents metric measures the average data quality of datasets, while the Active Daily Users metric measures user activity across data platforms.

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Metrics Data Analytics Analytics Measurement 130

DataKitchen

OCTOBER 11, 2021

Based on business rules, additional data quality tests check the dimensional model after the ETL job completes. While implementing a DataOps solution, we make sure that the pipeline has enough automated tests to ensure data quality and reduce the fear of failure. Adding Tests to Reduce Stress.

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Testing Metadata Dashboards Statistics 152

CIO Business Intelligence

JANUARY 31, 2023

Telecommunications, manufacturing, retail, publishing, and others have seen amazing changes in terms of new opportunities, capabilities, and efficiencies. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

Deep Learning 103

Deep Learning Cost-Benefit Data-driven Manufacturing 103

CIO Business Intelligence

DECEMBER 19, 2023

Third, in the CDO Agenda: 2024: Navigating Data and Generative AI Frontiers , 57% of respondents haven’t changed their data environments to support generative AI.

Digital Transformation 142

Digital Transformation Unstructured Data Machine Learning Risk Management 142

CIO Business Intelligence

MARCH 9, 2022

Some examples include: Customer 360 analytics, retail inventory and sales analysis, manufacturing operational analysis, eCommerce fraud prevention, network security intelligence, data warehouse consolidation and discount pricing optimization. Ready to evolve your analytics strategy or improve your data quality?

Data-driven 94

Data-driven Analytics Machine Learning Optimization 94

CIO Business Intelligence

JANUARY 9, 2024

After generative AI burst onto the scene, Nicholas Colisto, senior vice president and CIO of multinational manufacturer Avery Dennison, had worked to get his company to embrace its potential. “AI Can the current state of our data operations deliver the results we seek? What can we reasonably achieve given resource constraints?

IT 129

IT Risk Cost-Benefit Enterprise 129

Laminar Security

DECEMBER 13, 2023

Navigating the challenges of AI in data discovery and classification In the complex and dynamic landscape of data security, AI has emerged as a powerful tool for data discovery and classification. One of the primary challenges is data quality. However, it’s not without its challenges.

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Data-driven Machine Learning Risk Deep Learning 119

erwin

MARCH 21, 2019

Without it, they have to juggle multiple versions as changes to the underlying data aren’t automatically updated across the platform. A central metadata repository ensures an organization can acknowledge and get behind a single source of truth. Three Key Questions to Ask When Choosing a BPM Tool.

Modeling 75

Modeling Metadata IT Data Governance 75

Andrew White

OCTOBER 22, 2020

Industry Types: Manufacturing/Distribution 8. Topics : (broader/full) Data and Analytics Strategy 14. Data and Analytics Governance and/or MDM 10. Data and Analytics Governance Requires a Comprehensive Range of Policy Types. Toolkit: Data and Analytics Governance Role Descriptions. Grocery / Food and Beverage 4.

IT 52

IT Recreation/Entertainment Data Quality Data-driven 52

Octopai

AUGUST 3, 2022

It’s also a critical trait for the data assets of your dreams. What is data with integrity? Data integrity is the extent to which you can rely on a given set of data for use in decision-making. Increased data quality, accessibility, alignment across systems, and context all contribute to increased data integrity.

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Data Integration Manufacturing Data Quality Data Governance 93

Andrew White

OCTOBER 23, 2020

Manufacturing/Distribution 14. Topics : (broader/full) Data and Analytics Strategy 20. Data and Analytics Governance and/or MDM 15. And associated recorded webinar Drill-down on the “link data to outcome” idea we recommend to prioritize how to connect the teams around shared outcomes. Higher Education 3. Bio/Pharma 1.

IT 52

IT Digital Transformation Recreation/Entertainment Data Quality 52