ODSC - Open Data Science

APRIL 28, 2023

As critical data flows across an organization from various business applications, data silos become a big issue. The data silos, missing data, and errors make data management tedious and time-consuming, and they’re barriers to ensuring the accuracy and consistency of your data before it is usable by AI/ML.

ML 98

ML ML Data Silos AI 98

Precisely

SEPTEMBER 8, 2023

For data teams, that often leads to a burgeoning inbox of new projects, as business users throughout the organization strive to discover new insights and find new ways of creating value for the business. In the meantime, data quality and overall data integrity suffer from neglect.

Data Governance 52

Data Governance Data Quality Data Silos Big Data 52

Dataversity

AUGUST 4, 2023

Generating actionable insights across growing data volumes and disconnected data silos is becoming increasingly challenging for organizations. Working across data islands leads to siloed thinking and the inability to implement critical business initiatives such as Customer, Product, or Asset 360.

Data Silos 98

Data Silos Data Governance Data Quality 98

Precisely

JANUARY 17, 2023

Data integrity trends for 2023, has agility toping the list of success factors for most firms, as business leaders focus on rapid time to value and an emphasis on responding quickly to emerging opportunities and threats. With these goals in mind, access to accurate, consistent, and contextual information is critical.

Data Quality 97

Data Quality Machine Learning Machine Learning Data Silos 97

IBM Data Science in Practice

NOVEMBER 28, 2022

Insights from data gathered across business units improve business outcomes, but having heterogeneous data from disparate applications and storages makes it difficult for organizations to paint a big picture. How can organizations get a holistic view of data when it’s distributed across data silos?

Data Pipeline 130

Data Pipeline Data Quality Data Preparation Data Governance 130

Dataversity

FEBRUARY 6, 2023

Organizations seeking responsive and sustainable solutions to their growing data challenges increasingly lean on architectural approaches such as data mesh to deliver information quickly and efficiently.

Data Silos 52

Data Silos Data Quality Cloud Data 52

Precisely

SEPTEMBER 12, 2023

As a proud member of the Connect with Confluent program , we help organizations going through digital transformation and IT infrastructure modernization break down data silos and power their streaming data pipelines with trusted data. Let’s cover some additional information to know before attending.

Data Silos 52

Data Silos Apache Kafka Data Pipeline Data Quality 52

Precisely

JUNE 2, 2023

As companies strive to leverage AI/ML, location intelligence, and cloud analytics into their portfolio of tools, siloed mainframe data often stands in the way of forward momentum. Insufficient skills, limited budgets, and poor data quality also present significant challenges. To learn more, read our ebook.

Data Silos 52

Data Silos ETL Data Quality Data Pipeline 52

Precisely

MAY 16, 2024

You need to break down data silos and integrate critical data from all relevant sources into Amazon Web Services (AWS). Fuel your AI applications with trusted data to power reliable results. Add context to your data for more relevant and nuanced responses. You’re not alone.

AI 69

AI AI AWS Data Quality 69

Alation

APRIL 13, 2021

Much of his work focuses on democratising data and breaking down data silos to drive better business outcomes. In this blog, Chris shows how Snowflake and Alation together accelerate data culture. He shows how Texas Mutual Insurance Company has embraced data governance to build trust in data.

Data Governance 98

Data Governance Data Silos Data Quality 98

Alation

OCTOBER 5, 2021

It’s on Data Governance Leaders to identify the issues with the business process that causes users to act in these ways. Inconsistencies in expectations can create enormous negative issues regarding data quality and governance. Roadblock #3: Silos Breed Misunderstanding. Picking the Right Data Governance Tools.

Data Governance 96

Data Governance Data Quality Data Silos Analytics 96

Precisely

JANUARY 25, 2023

Data Integrity checks and best practices support data management as both strategic and tactical processes that enable companies to improve compliance, reduce costs, transform their customer relationships, and stay on the leading edge of innovation. This post examines the practical implications of poor data integrity.

Data Quality 52

Data Quality Machine Learning Machine Learning Data Silos 52

Dataversity

OCTOBER 25, 2021

It’s common for enterprises to run into challenges such as lack of data visibility, problems with data security, and low Data Quality. But despite the dangers of poor data ethics and management, many enterprises are failing to take the steps they need to ensure quality Data Governance.

Data Governance 98

Data Governance Data Quality Data Silos Cloud Data 98

Precisely

FEBRUARY 12, 2024

Despite that fact, valuable data often remains locked up in various silos across the organization. Specialized audiences may have access to it, but the organization lacks the necessary mechanisms to share that information across the enterprise. This shortfall in effective data governance inhibits visibility and transparency.

Data Governance 64

Data Governance Analytics Analytics Machine Learning 64

ODSC - Open Data Science

JULY 13, 2023

While gathering operational and consumer information can benefit businesses, they often face obstacles. Some of the top data challenges in the retail industry involve collection and application. Gathering massive amounts of information can be relatively easy, but properly utilizing it can be complex, leading to these data challenges.

Data Science 52

Data Science Machine Learning Machine Learning Data Silos 52

IBM Journey to AI blog

JANUARY 25, 2023

While operational data runs day-to-day business operations, gaining insights and leveraging data across business processes and workflows presents a well-known set of data governance challenges that technology alone cannot solve. Silos exist naturally when data is managed by multiple operational systems.

Data Governance 52

Data Governance Data Silos Data Quality Analytics 52

Dataversity

DECEMBER 24, 2020

.” The series covers some of the most prominent questions in Data Management such as Master Data, the difference between Master Data and MDM, “truth” versus “meaning” in data, Data Quality, and so much […].

Data Quality 97

Data Quality Data Silos Data Governance 97

Dataversity

AUGUST 7, 2023

In the era of digital transformation, data has become the new oil. Businesses increasingly rely on real-time data to make informed decisions, improve customer experiences, and gain a competitive edge. However, managing and handling real-time data can be challenging due to its volume, velocity, and variety.

Data Silos 98

Data Silos Data Quality Cloud Data Analytics 98

Dataversity

OCTOBER 22, 2021

.” The series covers some of the most prominent questions in Data Management, such as master data, the difference between master data and MDM, “truth” versus “meaning” in data, Data Quality, and so much more. […].

Data Quality 52

Data Quality Data Silos Data Governance 52

Dataconomy

MARCH 29, 2023

In an era where data is king, the ability to harness and manage it effectively can make or break a business. A comprehensive data governance strategy is the foundation upon which organizations can build trust with their customers, stay compliant with regulations, and drive informed decision-making.

Data Governance 70

Data Governance Data Analyst Data Quality Data Silos 70

Dataconomy

MARCH 29, 2023

In an era where data is king, the ability to harness and manage it effectively can make or break a business. A comprehensive data governance strategy is the foundation upon which organizations can build trust with their customers, stay compliant with regulations, and drive informed decision-making.

Data Governance 70

Data Governance Data Analyst Data Quality Data Silos 70

Alation

APRIL 27, 2023

It’s a subject that’s giving many of us from the data warehouse generation a serious case of agita. Concerns about an unmanageable explosion of data silos , inconsistent data quality , and multiple versions of universal data that should be common to all domains, are justified. master data?

Data Warehouse 52

Data Warehouse Data Silos Data Governance Data Quality 52

IBM Journey to AI blog

JANUARY 15, 2024

It introduced Robotic Process Automation (RPA) in pilot scenarios to swiftly enhance process efficiency and quality, integrating system resources cost-effectively and breaking data silos. The company also recognized data issues and introduced measures to ensure continuous and effective data quality oversight.

Data Silos 70

Data Silos AI AI Artificial Intelligence 70

Pickl AI

APRIL 14, 2023

With the exponential growth of data and increasing complexities of the ecosystem, organizations face the challenge of ensuring data security and compliance with regulations. Enhances Transparency Transparency while documenting data is important. This establishes data accountability. Wrapping it up !!!

Data Governance 52

Data Governance Data Quality Data Silos Analytics 52

Dataversity

APRIL 23, 2021

Within the Data Management industry, it’s becoming clear that the old model of rounding up massive amounts of data, dumping it into a data lake, and building an API to extract needed information isn’t working. It’s outdated, it’s clunky, and it was built for a different era. […].

Database 90

Database Data Lakes Data Silos Data Governance 90

Alation

APRIL 27, 2023

It’s a subject that’s giving many of us from the data warehouse generation a serious case of agita. Concerns about an unmanageable explosion of data silos , inconsistent data quality , and multiple versions of universal data that should be common to all domains, are justified. master data?

Data Warehouse 40

Data Warehouse Data Silos Data Governance Data Quality 40

Heartbeat

DECEMBER 7, 2023

Data should have an independent team responsible for its creation, delivery, and sustainability. This team should consist of experts who know the business domain where the data comes from and should be something other than general-purpose Information and Communication Technologies (ICT) teams. What is Data Mesh?

Data Governance 52

Data Governance Deep Learning Deep Learning Artificial Intelligence 52

AWS Machine Learning Blog

MARCH 15, 2024

This approach can help heart stroke patients, doctors, and researchers with faster diagnosis, enriched decision-making, and more informed, inclusive research work on stroke-related health issues, using a cloud-native approach with AWS services for lightweight lift and straightforward adoption. Much of this work comes down to the data.”

AWS 93

AWS ML ML Data Silos 93

Precisely

MARCH 4, 2024

Let’s explore how to harness the full potential of AI technologies by making your data AI-ready. The Risks of Rushing Without Readiness The power of AI isn’t just in its ability to process information at an unprecedented scale but in doing so with accuracy and integrity that you can rely on.

AI 72

AI AI Data Quality Artificial Intelligence 72

Alation

MAY 31, 2023

How is the data architecture role evolving? As data governance gains importance, data architects must work with data stewards and owners to establish policies, develop governance frameworks, implement data quality programs, and provide guidance to other data professionals.

Data Governance 52

Data Governance Data Quality Data Silos Data Modeling 52

Dataversity

AUGUST 5, 2021

According to Gartner, data fabric is an architecture and set of data services that provides consistent functionality across a variety of environments, from on-premises to the cloud. Data fabric simplifies and integrates on-premises and cloud Data Management by accelerating digital transformation.

Cloud Data 98

Cloud Data Data Silos Data Lakes Data Warehouse 98

Tableau

APRIL 18, 2022

What if the problem isn’t in the volume of data, but rather where it is located—and how hard it is to gather? Nine out of 10 IT leaders report that these disconnects, or data silos, create significant business challenges.* Analytics data catalog. Data quality and lineage. Metadata management. Orchestration.

Tableau 99

Tableau Data Quality Analytics Analytics 99

Tableau

APRIL 18, 2022

What if the problem isn’t in the volume of data, but rather where it is located—and how hard it is to gather? Nine out of 10 IT leaders report that these disconnects, or data silos, create significant business challenges.* Analytics data catalog. Data quality and lineage. Metadata management. Orchestration.

Tableau 97

Tableau Data Quality Analytics Analytics 97

phData

SEPTEMBER 20, 2023

A data mesh is a decentralized approach to data architecture that’s been gaining traction as a solution to the challenges posed by large and complex data ecosystems. It’s all about breaking down data silos, empowering domain teams to take ownership of their data, and fostering a culture of data collaboration.

Data Silos 52

Data Silos Database Data Quality Data Engineering 52

Alation

MARCH 21, 2023

While this industry has used data and analytics for a long time, many large travel organizations still struggle with data silos , which prevent them from gaining the most value from their data. What is big data in the travel and tourism industry? What is big data in the travel and tourism industry?

Analytics 52

Analytics Analytics Data Silos Big Data 52

Dataversity

FEBRUARY 11, 2022

As organizations enter a new year, leaders across industries are increasingly collecting more data to drive innovative growth strategies. Yet to move forward effectively, these organizations need greater context around their data to make accurate and streamlined decisions.

Data Silos 52

Data Silos Data Quality Data Governance 52

Dataversity

APRIL 25, 2022

Data collection, while crucial to the overall functionality and health of a business, does not automatically lead to success. If data processes are not at peak performance and efficiency, businesses are just collecting massive stores of data for no reason. Effective use […].

Data Observability 52

Data Observability Data Silos Data Quality Data Governance 52