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.

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IBM Journey to AI blog

JANUARY 23, 2023

Simply put, data governance is the process of establishing policies, procedures, and standards for managing data within an organization. It involves defining roles and responsibilities, setting standards for data quality, and ensuring that data is being used in a way that is consistent with the organization’s goals and values.

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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.

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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?

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Precisely

JANUARY 17, 2023

As they do so, access to traditional and modern data sources is required. Poor data quality and information silos tend to emerge as early challenges. Customer data quality, for example, tends to erode very quickly as consumers experience various life changes.

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Precisely

JUNE 26, 2023

Those who have already made progress toward that end have used advanced analytics tools that work outside of their application-based data silos. Successful organizations also developed intentional strategies for improving and maintaining data quality at scale using automated tools. The biggest surprise?

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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. Book your meeting with us at Confluent’s Current 2023. See you in San Jose!

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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.

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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.

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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.

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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.

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Women in Big Data

FEBRUARY 1, 2023

She goes on to explain the one of the most beneficial features of One Data’s enabling technology, One Data Cartography , is record linkage combined with data quality. This feature enables holistic and seamless data tracking across system boundaries, based on algorithms and automatic checks for quality anomalies.

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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.

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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 […].

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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.

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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.

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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. […].

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Precisely

FEBRUARY 2, 2023

This requires access to data from across business systems when they need it. Data silos and slow batch delivery of data will not do. Stale data and inconsistencies can distort the perception of what is really happening in the business leading to uncertainty and delay.

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Precisely

FEBRUARY 12, 2024

That means having data that can be trusted to deliver on the organization’s strategic and tactical objectives, producing positive outcomes in network planning and optimization, improving customer experiences, reaching new subscribers, and achieving corporate sustainability goals.

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Pickl AI

DECEMBER 4, 2023

Data governance and security Like a fortress protecting its treasures, data governance, and security form the stronghold of practical Data Intelligence. Think of data governance as the rules and regulations governing the kingdom of information. It ensures data quality , integrity, and compliance.

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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.

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ODSC - Open Data Science

JULY 13, 2023

Instead of broadly applying their knowledge to all stores or customers, they must have a strategy to ensure data quality. A retailer must connect data silos across the entire organization for proper consolidation. While standardization can be beneficial, ensuring their actions are applicable is essential.

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Dataconomy

MARCH 29, 2023

It involves the creation of rules for collecting, storing, processing, and sharing data to ensure its accuracy, completeness, consistency, and security. Some key concepts related to data governance include: Data quality:  Ensuring that data is accurate, complete, and consistent.

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Dataconomy

MARCH 29, 2023

It involves the creation of rules for collecting, storing, processing, and sharing data to ensure its accuracy, completeness, consistency, and security. Some key concepts related to data governance include: Data quality:  Ensuring that data is accurate, complete, and consistent.

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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. Although Data Governance is not mandatory, it works with data quality and Master Data Management Tools.

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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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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.

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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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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.

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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.

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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.

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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.

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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

MARCH 4, 2024

How it’s done : An AI recommender system is a sophisticated technology that leverages AI and vast amounts of user data – like past preferences, behaviors, and interactions – to suggest tailored products, content, or services. You need to break down data silos and integrate critical data from all relevant sources.

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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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AWS Machine Learning Blog

MARCH 15, 2024

Duration of data informs on long-term variations and patterns in the dataset that would otherwise go undetected and lead to biased and ill-informed predictions. Breaking down these data silos to unite the untapped potential of the scattered data can save and transform many lives. Much of this work comes down to the data.”

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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.

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