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.

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Precisely

NOVEMBER 11, 2024

This involves integrating customer data across various channels – like your CRM systems, data warehouses, and more – so that the most relevant and up-to-date information is used consistently in your customer interactions. Focus on high-quality data. Data quality is essential for personalization efforts.

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Precisely

NOVEMBER 11, 2024

This involves integrating customer data across various channels – like your CRM systems, data warehouses, and more – so that the most relevant and up-to-date information is used consistently in your customer interactions. Focus on high-quality data. Data quality is essential for personalization efforts.

Data Silos 52

Data Silos Data Warehouse Artificial Intelligence Artificial Intelligence 52

Alation

OCTOBER 5, 2021

Without a doubt, no company can achieve lasting profitability and sustainable growth with a poorly constructed data governance methodology. Today, all companies must pursue data analytics, Machine Learning & Artificial Intelligence (ML & AI) as an integral part of any standard business plan.

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Precisely

JUNE 26, 2023

They shore up privacy and security, embrace distributed workforce management, and innovate around artificial intelligence and machine learning-based automation. The key to success within all of these initiatives is high-integrity data. Only 46% of respondents rate their data quality as “high” or “very high.”

Data Quality 52

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Precisely

SEPTEMBER 26, 2024

Key Takeaways: Trusted AI requires data integrity. For AI-ready data, focus on comprehensive data integration, data quality and governance, and data enrichment. Building data literacy across your organization empowers teams to make better use of AI tools. The impact?

AI 75

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Precisely

MARCH 4, 2024

What if every decision, recommendation, and prediction made by artificial intelligence (AI) was as reliable as your most trusted team members? Next, you’ll see valuable AI use cases and how data integrity powers success. Technology-driven insights and capabilities depend on trusted data.

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IBM Journey to AI blog

SEPTEMBER 5, 2024

Access to high-quality data can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success. Emerging technologies and trends, such as machine learning (ML), artificial intelligence (AI), automation and generative AI (gen AI), all rely on good data quality.

Data Governance 75

Data Governance Data Quality DataOps Artificial Intelligence 75

AWS Machine Learning Blog

MARCH 15, 2024

Federation learning to save the day (and save lives) For good artificial intelligence (AI), you need good data. Legacy systems, which are frequently found in the federal domain, pose significant data processing challenges before you can derive any intelligence or merge them with newer datasets.

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Precisely

MAY 16, 2024

When you think about the potential of artificial intelligence (AI) for your business, what comes to mind? 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.

AI 69

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IBM Journey to AI blog

JULY 3, 2024

Open is creating a foundation for storing, managing, integrating and accessing data built on open and interoperable capabilities that span hybrid cloud deployments, data storage, data formats, query engines, governance and metadata. Effective data quality management is crucial to mitigating these risks.

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Pickl AI

DECEMBER 4, 2023

In the realm of Data Intelligence, the blog demystifies its significance, components, and distinctions from Data Information, Artificial Intelligence, and Data Analysis. Think of data governance as the rules and regulations governing the kingdom of information. Look at the table below.

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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 85

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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?

Analytics 52

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Precisely

FEBRUARY 12, 2024

Here are some of the key trends and challenges facing telecommunications companies today: The growth of AI and machine learning: Telecom companies use artificial intelligence and machine learning (AI/ML) for predictive analytics and network troubleshooting.

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ODSC - Open Data Science

JULY 13, 2023

A machine learning scientist or artificial intelligence (AI) technology is an excellent candidate for the role. Instead of broadly applying their knowledge to all stores or customers, they must have a strategy to ensure data quality. They can use it to properly inform their marketing and financial actions.

Data Science 52

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IBM Journey to AI blog

JANUARY 17, 2023

The rapid growth of data continues to proceed unabated and is now accompanied by not only the issue of siloed data but a plethora of different repositories across numerous clouds. From there, it can be easily accessed via dashboards by data consumers or those building into a data product. Start a trial.

Data Governance 58

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IBM Journey to AI blog

MAY 15, 2024

Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges. This situation will exacerbate data silos, increase costs and complicate the governance of AI and data workloads.

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IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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Flipboard

FEBRUARY 12, 2025

Artificial intelligence (AI) is accelerating at an astonishing pace, quickly moving from emerging technologies to impacting how businesses run. This will only worsen, and companies must learn to adapt their models to unique, content-rich data sources. But what exactly lies ahead?

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Heartbeat

DECEMBER 7, 2023

What is Data Mesh? Data Mesh is a new data set that enables units or cross-functional teams to decentralize and manage their data domains while collaborating to maintain data quality and consistency across the organization — architecture and governance approach. We can call fabric texture or actual fabric.

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Pickl AI

JULY 16, 2024

Enter AIOps, a revolutionary approach leveraging Artificial Intelligence (AI) to automate and optimize IT operations. Imagine an IT team empowered with a proactive assistant, constantly analysing vast amounts of data to anticipate problems, automate tasks, and resolve issues before they disrupt operations.

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Pickl AI

JUNE 13, 2024

Here, we have highlighted the concerning issues like usability, data quality, and clinician trust. Data Quality The accuracy of CDSS recommendations hinges on the quality of patient data fed into the system. This can create data silos and hinder the flow of information within a healthcare organization.

Big Data Analytics 52

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ODSC - Open Data Science

SEPTEMBER 29, 2023

A 2019 survey by McKinsey on global data transformation revealed that 30 percent of total time spent by enterprise IT teams was spent on non-value-added tasks related to poor data quality and availability. The data lake can then refine, enrich, index, and analyze that data.

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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 […].

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AWS Machine Learning Blog

APRIL 3, 2025

By analyzing their data, organizations can identify patterns in sales cycles, optimize inventory management, or help tailor products or services to meet customer needs more effectively. The company aims to integrate additional data sources, including other mission-critical systems, into ODAP.

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Precisely

FEBRUARY 9, 2024

In 2023, organizations dealt with more data than ever and witnessed a surge in demand for artificial intelligence use cases – particularly driven by generative AI. They relied on their data as a critical factor to guide their businesses to agility and success.

Data Quality 69

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Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

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Dataconomy

MARCH 18, 2025

What is continuous intelligence? Continuous intelligence is the real-time analysis and processing of data streams to enable automated decision-making and insights. Continuous intelligence represents an evolution in the realm of data analytics.

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Pickl AI

DECEMBER 3, 2024

By leveraging GenAI, businesses can personalize customer experiences and improve data quality while maintaining privacy and compliance. Introduction Generative AI (GenAI) is transforming Data Analytics by enabling organisations to extract deeper insights and make more informed decisions. What is Generative AI?

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