IBM Journey to AI blog

SEPTEMBER 5, 2024

The best way to build a strong foundation for data success is through effective data governance. Access to high-quality data can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success.

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IBM Journey to AI blog

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

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Dataversity

SEPTEMBER 21, 2021

In my first business intelligence endeavors, there were data normalization issues; in my Data Governance period, Data Quality and proactive Metadata Management were the critical points. The post The Declarative Approach in a Data Playground appeared first on DATAVERSITY. But […].

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IBM Journey to AI blog

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

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DagsHub

AUGUST 23, 2024

As such, the quality of their data can make or break the success of the company. This article will guide you through the concept of a data quality framework, its essential components, and how to implement it effectively within your organization. What is a data quality framework?

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Alation

AUGUST 5, 2021

What is Data Quality? Data quality is defined as: the degree to which data meets a company’s expectations of accuracy, validity, completeness, and consistency. By tracking data quality , a business can pinpoint potential issues harming quality, and ensure that shared data is fit to be used for a given purpose.

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Alation

SEPTEMBER 7, 2021

In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. So why are organizations not able to scale governance? Meet Governance Requirements.

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Dataversity

AUGUST 12, 2024

We live in a data-driven culture, which means that as a business leader, you probably have more data than you know what to do with. To gain control over your data, it is essential to implement a data governance strategy that considers the business needs of every level, from basement to boardroom.

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Precisely

MARCH 14, 2023

And the desire to leverage those technologies for analytics, machine learning, or business intelligence (BI) has grown exponentially as well. Now, almost any company can build a solid, cost-effective data analytics or BI practice grounded in these new cloud platforms. Cloud-native data execution is just the beginning.

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The Data Administration Newsletter

JANUARY 15, 2025

In my journey as a data management professional, Ive come to believe that the road to becoming a truly data-centric organization is paved with more than just tools and policies its about creating a culture where data literacy and business literacy thrive.

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Alation

MAY 31, 2023

The Data Governance & Information Quality Conference (DGIQ) is happening soon — and we’ll be onsite in San Diego from June 5-9. If you’re not familiar with DGIQ, it’s the world’s most comprehensive event dedicated to, you guessed it, data governance and information quality. The best part?

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Alation

JANUARY 26, 2023

These data requirements could be satisfied with a strong data governance strategy. Governance can — and should — be the responsibility of every data user, though how that’s achieved will depend on the role within the organization. Low quality In many scenarios, there is no one responsible for data administration.

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Dataconomy

SEPTEMBER 4, 2023

Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence. Understand what insights you need to gain from your data to drive business growth and strategy.

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Smart Data Collective

DECEMBER 21, 2022

Big data technology has helped businesses make more informed decisions. A growing number of companies are developing sophisticated business intelligence models, which wouldn’t be possible without intricate data storage infrastructures. One of the biggest issues pertains to data quality.

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Precisely

APRIL 25, 2024

Jean-Paul sat down for an interview where we discussed his background as a former CDO, the challenges he faced, and how he developed his unique perspective and data governance expertise. After starting my career in banking IT, I turned to consulting, and more specifically to Business Intelligence (BI) in 2004.

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Defined.ai blog

AUGUST 10, 2023

For example, if your AI model were designed to predict future sales based on past data, the output would likely be a predictive score. This score represents the predicted sales, and its accuracy would depend on the data quality and the AI model’s efficiency. Maintaining data quality.

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Alation

JULY 19, 2021

This requires a metadata management solution to enable data search & discovery and data governance, both of which empower access to both the metadata and the underlying data to those who need it. In today’s world, metadata management best practices call for a data catalog. Administrative information.

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Data Science Dojo

JANUARY 12, 2023

Analytics Data lakes give various positions in your company, such as data scientists, data developers, and business analysts, access to data using the analytical tools and frameworks of their choice. You can perform analytics with Data Lakes without moving your data to a different analytics system. 4.

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The Data Administration Newsletter

OCTOBER 3, 2023

My recent columns have focused on actionable initiatives that can both deliver business value, providing a tangible achievement, and raise the profile of the data management organization data management organization (DMO).(For In that light, let’s […]

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IBM Journey to AI blog

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

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Dataversity

JULY 21, 2022

Despite its many benefits, the emergence of high-performance machine learning systems for augmented analytics over the last 10 years has led to a growing “plug-and-play” analytical culture, where high volumes of opaque data are thrown arbitrarily at an algorithm until it yields useful business intelligence.

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The Data Administration Newsletter

DECEMBER 20, 2022

Over the past few months, my team in Castlebridge and I have been working with clients delivering training to business and IT teams on data management skills like data governance, data quality management, data modelling, and metadata management.

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Pickl AI

OCTOBER 10, 2024

Summary: Data transformation tools streamline data processing by automating the conversion of raw data into usable formats. These tools enhance efficiency, improve data quality, and support Advanced Analytics like Machine Learning.

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Dataversity

AUGUST 16, 2023

Various factors have moved along this evolution, ranging from widespread use of cloud services to the availability of more accessible (and affordable) data analytics and business intelligence tools.

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IBM Journey to AI blog

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

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ODSC - Open Data Science

SEPTEMBER 27, 2023

Storage Optimization: Data warehouses use columnar storage formats and indexing to enhance query performance and data compression. Without proper version control, different users may inadvertently overwrite or modify data, leading to potential data integrity issues and confusion.

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IBM Journey to AI blog

OCTOBER 12, 2023

Accounting for the complexities of the AI lifecycle Unfortunately, typical data storage and data governance tools fall short in the AI arena when it comes to helping an organization perform the tasks that underline efficient and responsible AI lifecycle management. And that makes sense.

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Alation

OCTOBER 21, 2021

Data lakes also support the growing thirst for analysis by data scientists and data analysts, as well as the critical role of data governance. But setting up a data lake takes a thoughtful approach to ensure it’s positioned to prevent it from becoming a data swamp. Irrelevant data.

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The Data Administration Newsletter

DECEMBER 5, 2023

In part one of “Metadata Governance: An Outline for Success,” I discussed the steps required to implement a successful data governance environment, what data to gather to populate the environment, and how to gather the data.

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Data Science Dojo

AUGUST 24, 2023

Better model performance : With MLOps, businesses can continuously monitor and improve the performance of their ML models. MLOps facilitates automated testing mechanisms for ML models, which detects problems related to model accuracy, model drift, and data quality.

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Pickl AI

DECEMBER 2, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. Analytics tools help convert raw data into actionable insights for businesses. Strong data governance ensures accuracy, security, and compliance in data management. What is Big Data?

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Pickl AI

NOVEMBER 25, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. Analytics tools help convert raw data into actionable insights for businesses. Strong data governance ensures accuracy, security, and compliance in data management. What is Big Data?

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Pickl AI

AUGUST 11, 2024

Additionally, it addresses common challenges and offers practical solutions to ensure that fact tables are structured for optimal data quality and analytical performance. Introduction In today’s data-driven landscape, organisations are increasingly reliant on Data Analytics to inform decision-making and drive business strategies.

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Dataversity

FEBRUARY 19, 2021

Enterprises are modernizing their data platforms and associated tool-sets to serve the fast needs of data practitioners, including data scientists, data analysts, business intelligence and reporting analysts, and self-service-embracing business and technology personnel.

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IBM Journey to AI blog

JULY 3, 2024

Multiple data applications and formats make it harder for organizations to access, govern, manage and use all their data for AI effectively. Scaling data and AI with technology, people and processes Enabling data as a differentiator for AI requires a balance of technology, people and processes.

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Alation

MARCH 8, 2022

To maintain trust and confidence, it’s critical that self-service data instills a level of trust so workers can get the data they need and make quick, confident decisions. Connects BI to data science tools. You’ll need talented data experts, but may find a shortage as they’re in high demand.

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Dataversity

FEBRUARY 1, 2021

In Part 1 and Part 2 of this series, we described how data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations. Project sponsors seek to empower more and better data-driven decisions and actions throughout their enterprise; they intend to expand their […].

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