Dataconomy

APRIL 16, 2025

Analytics engines: Systems that process data and execute complex analyses, from basic queries to advanced algorithms. AI/ML capabilities: Incorporates artificial intelligence and machine learning to enhance forecasting and predictive analytics.

Analytics 91

Analytics Analytics Data Analysis Data Analysis 91

Smart Data Collective

OCTOBER 20, 2021

For people striving to rule the data integration and data management world, it should not be a surprise that companies are facing difficulty in accessing and integrating data across system or application data silos. The role of Artificial Intelligence and Machine Learning comes into play here.

ML 133

ML ML Big Data Big Data 133

Flipboard

JUNE 5, 2023

True data quality simplification requires transformation of both code and data, because the two are inextricably linked. Code sprawl and data siloing both imply bad habits that should be the exception, rather than the norm.

Data Quality 121

Data Quality Data Silos Big Data Big Data 121

Dataconomy

JUNE 1, 2023

Unified data storage : Fabric’s centralized data lake, Microsoft OneLake, eliminates data silos and provides a unified storage system, simplifying data access and retrieval. This open format allows for seamless storage and retrieval of data across different databases.

Power BI 194

Power BI Data Lakes Azure Data Silos 194

Pickl AI

JULY 24, 2024

Summary: Data quality is a fundamental aspect of Machine Learning. Poor-quality data leads to biased and unreliable models, while high-quality data enables accurate predictions and insights. What is Data Quality in Machine Learning? What is Data Quality in Machine Learning?

Data Quality 52

Data Quality Machine Learning Machine Learning Clean Data 52

Precisely

DECEMBER 16, 2024

AIOps, or artificial intelligence for IT operations, combines AI technologies like machine learning, natural language processing, and predictive analytics, with traditional IT operations. Tool overload can lead to inefficiencies and data silos. Understanding AI Operations (AIOps) in IT Environments What is AIOps?

Artificial Intelligence 59

Artificial Intelligence Artificial Intelligence Data Silos Machine Learning 59

Dataconomy

OCTOBER 4, 2023

It also allows for decision-making by connecting existing data silos within organizations. The technologies that support systems to meet the above requirements are the Industrial Internet of Things , Machine Learning, and the public cloud.

Internet of Things 202

Internet of Things Machine Learning Machine Learning Data Silos 202

Dataconomy

OCTOBER 4, 2023

It also allows for decision-making by connecting existing data silos within organizations. The technologies that support systems to meet the above requirements are the Industrial Internet of Things, Machine Learning, and the public cloud.

Internet of Things 202

Internet of Things Machine Learning Machine Learning Data Silos 202

Flipboard

NOVEMBER 22, 2024

This post is part of an ongoing series about governing the machine learning (ML) lifecycle at scale. This post dives deep into how to set up data governance at scale using Amazon DataZone for the data mesh. To view this series from the beginning, start with Part 1.

Data Governance 130

Data Governance ML ML Data Lakes 130

Dataversity

FEBRUARY 17, 2022

With machine learning (ML) and artificial intelligence (AI) applications becoming more business-critical, organizations are in the race to advance their AI/ML capabilities. To realize the full potential of AI/ML, having the right underlying machine learning platform is a prerequisite.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

SEPTEMBER 12, 2024

Introduction Machine Learning has evolved significantly, from basic algorithms to advanced models that drive today’s AI innovations. A key advancement is Federated Learning, which enhances privacy and efficiency by training models across decentralised devices. What is Federated Learning?

Machine Learning 52

Machine Learning Machine Learning Clustering Algorithm 52

Flipboard

MAY 14, 2025

Amazon QuickSight is a comprehensive Business Intelligence (BI) environment that offers a range of advanced features for data analysis and visualization. This unified solution transforms hours of manual data aggregation into instant insights using natural language queries while maintaining robust security and permissions.

AWS 139

AWS AI AI Database 139

ODSC - Open Data Science

APRIL 28, 2023

Be sure to check out her talk, “ Power trusted AI/ML Outcomes with Data Integrity ,” there! Due to the tsunami of data available to organizations today, artificial intelligence (AI) and machine learning (ML) are increasingly important to businesses seeking competitive advantage through digital transformation.

ML 98

ML ML Data Silos Data Quality 98

AWS Machine Learning Blog

DECEMBER 29, 2022

You can quickly launch the familiar RStudio IDE and dial up and down the underlying compute resources without interrupting your work, making it easy to build machine learning (ML) and analytics solutions in R at scale. Now let’s prepare a dataset that could be used for machine learning. arrange(card_brand).

AWS 135

AWS Machine Learning Machine Learning Clustering 135

AWS Machine Learning Blog

MARCH 15, 2024

Many organizations are implementing machine learning (ML) to enhance their business decision-making through automation and the use of large distributed datasets. With increased access to data, ML has the potential to provide unparalleled business insights and opportunities. In such scenarios, you can use FedML Octopus.

AWS 133

AWS ML ML Machine Learning 133

DrivenData Labs

MARCH 30, 2023

Privacy-enhancing technologies (PETs) have the potential to unlock more trustworthy innovation in data analysis and machine learning. Federated learning is one such technology that enables organizations to analyze sensitive data while providing improved privacy protections. What motivated you to participate?

Machine Learning 162

Machine Learning Machine Learning Data Science Algorithm 162

Dataconomy

MAY 26, 2025

Building robust architecture Creating a flexible data architecture ensures that the management system is able to adapt to evolving needs. Enhancing data accessibility Strategies to eliminate data silos are crucial for ensuring that data flows smoothly across various systems.

Big Data 91

Big Data Big Data Apache Hadoop Data Quality 91

AWS Machine Learning Blog

JANUARY 13, 2023

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at any single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository.

AWS 99

AWS Analytics Analytics Machine Learning 99

Flipboard

MAY 29, 2025

Danielle is VP of AI and Machine Learning at GSK (formerly GlaxoSmithKline). They discuss using AI and machine learning to get better diagnoses that reflect the differences between patients. Learn from their experience to help put AI to work in your enterprise. Danielle is our first guest representing Big Pharma.

AI 77

AI AI ML ML 77

Flipboard

JANUARY 7, 2025

Almost half of AI projects are doomed by poor data quality, inaccurate or incomplete data categorization, unstructured data, and data silos. Avoid these 5 mistakes

Data Silos 65

Data Silos Data Quality AI AI 65

AWS Machine Learning Blog

JUNE 16, 2025

Based in Seattle, WA, Takeshi is passionate about pushing the boundaries of artificial intelligence and machine learning technologies. With over 14 years of experience at Amazon in AWS, AI/ML, and technology, Takeshi is dedicated to leveraging generative AI and AWS services to build innovative solutions that address customer needs.

AWS 86

AWS ML ML AI 86

Precisely

DECEMBER 12, 2024

When integrated with AI, mainframe data has the potential to serve as a key asset in addressing one of the most persistent challenges in AIbias. Understanding Bias in AI Bias in AI arises when the data used to train machine learning models reflects historical inequalities, stereotypes, or inaccuracies.

AI 64

AI AI Algorithm Data Silos 64

AWS Machine Learning Blog

DECEMBER 3, 2024

Amazon Q Business is a generative AI-powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems.

AWS 98

AWS Database Data Silos Data Lakes 98

IBM Journey to AI blog

JANUARY 30, 2024

Multicloud architecture not only empowers businesses to choose a mix of the best cloud products and services to match their business needs, but it also accelerates innovation by supporting game-changing technologies like generative AI and machine learning (ML).

Cloud Computing 115

Cloud Computing Data Silos Azure AWS 115

Pickl AI

DECEMBER 3, 2024

Current Challenges in Data Analytics Despite the advancements in Data Analytics technologies, organisations face several challenges: Data Quality: Inconsistent or incomplete data can lead to inaccurate insights. Poor-quality data hampers decision-making and can result in significant financial losses.

Analytics 52

Analytics Analytics Data Quality AI 52

AWS Machine Learning Blog

JANUARY 13, 2023

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at a single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository.

AWS 95

AWS Analytics Analytics Machine Learning 95

Smart Data Collective

JUNE 3, 2019

The promise of significant and measurable business value can only be achieved if organizations implement an information foundation that supports the rapid growth, speed and variety of data. This integration is even more important, but much more complex with Big Data. Big Data is Transforming the Financial Industry.

Big Data 85

Big Data Big Data Data Silos AI 85

IBM Journey to AI blog

OCTOBER 18, 2024

Strong integration capabilities ensure smooth data flow between departments, eliminating data silos. Choose a solution that includes AI-driven insights as a core feature, enabling your business to leverage machine learning for more accurate forecasts and strategic planning. Flexibility is key.

Data Silos 101

Data Silos Analytics Analytics AI 101

Precisely

JANUARY 17, 2023

Technology helped to bridge the gap, as AI, machine learning, and data analytics drove smarter decisions, and automation paved the way for greater efficiency. AI and machine learning initiatives play an increasingly important role.

Data Quality 97

Data Quality Machine Learning Machine Learning Data Silos 97

ML @ CMU

MAY 12, 2023

Unfortunately, while this data contains a wealth of useful information for disease forecasting, the data itself may be highly sensitive and stored in disparate locations (e.g., In this post we discuss our research on federated learning , which aims to tackle this challenge by performing decentralized learning across private data silos.

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Data Silos Algorithm ML ML 130

IBM Journey to AI blog

APRIL 15, 2024

Organizations gain the ability to effortlessly modify and scale their data in response to shifting business demands, leading to greater agility and adaptability. A data virtualization platform breaks down data silos by using data virtualization.

Analytics 81

Analytics Analytics Data Silos AI 81

DataRobot Blog

FEBRUARY 28, 2023

Integrating different systems, data sources, and technologies within an ecosystem can be difficult and time-consuming, leading to inefficiencies, data silos, broken machine learning models, and locked ROI.

Exploratory Data Analysis 72

Exploratory Data Analysis ML ML AI 72

IBM Journey to AI blog

JUNE 15, 2023

There’s no debate that the volume and variety of data is exploding and that the associated costs are rising rapidly. The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights.

Data Warehouse 110

Data Warehouse Data Lakes Cloud Data Analytics 110

Precisely

AUGUST 12, 2024

Data silos Limited integration capabilities Fragmented communications Workflow problems Limited scalability The fact is, your legacy systems can create great risks for your business. A unified CXP can also provide real-time data insights, helping you understand customer preferences and behavior.

Data Silos 52

Data Silos Artificial Intelligence Artificial Intelligence ML 52

phData

APRIL 18, 2023

This is due to a fragmented ecosystem of data silos, a lack of real-time fraud detection capabilities, and manual or delayed customer analytics, which results in many false positives. Snowflake Marketplace offers data from leading industry providers such as Axiom, S&P Global, and FactSet.

Data Silos 52

Data Silos ETL Clustering Analytics 52

AWS Machine Learning Blog

MAY 16, 2025

One of the key challenges they face is managing the complexity of disparate business systems and workflows, which leads to inefficiencies, data silos, and missed opportunities.

AWS 68

AWS Data Silos AI AI 68

Analytics Vidhya

AUGUST 31, 2022

This article was published as a part of the Data Science Blogathon. Introduction A data lake is a central data repository that allows us to store all of our structured and unstructured data on a large scale.

Data Lakes 271

Data Lakes Big Data Big Data Data Science 271