Dataversity

DECEMBER 7, 2021

Robert Seiner and Anthony Algmin faced off – in a virtual sense – at the DATAVERSITY® Enterprise Data World Conference to determine which is more important: Data Governance, Data Leadership, or Data Architecture. The post Data Governance, Data Leadership or Data Architecture: What Matters Most?

Data Governance 95

Data Governance Data Quality Business Intelligence Business Intelligence 95

Dataconomy

APRIL 21, 2023

In retail, complete and consistent data is necessary to understand customer behavior and optimize sales strategies. Without data fidelity, decision-makers cannot rely on data insights to make informed decisions. Poor data quality can result in wasted resources, inaccurate conclusions, and lost opportunities.

Data Quality 182

Data Quality Data Governance Data Visualization Power BI 182

Data Science Connect

JULY 22, 2024

Precisely offers data integrity, integration, and enrichment solutions to help businesses ensure accurate, consistent, and contextual data. Their products and services include data quality, location intelligence, data governance, and customer engagement solutions.

Data Governance 130

Data Governance Data Quality 130

Tableau

SEPTEMBER 23, 2021

If we asked you, “What does your organization need to help more employees be data-driven?” where would “better data governance” land on your list? We’re all trying to use more data to make decisions, but constantly face roadblocks and trust issues related to data governance. . A data governance framework.

Data Governance 97

Data Governance Analytics Analytics Tableau 97

IBM Data Science in Practice

APRIL 26, 2024

In this blog, we explore how the introduction of SQL Asset Type enhances the metadata enrichment process within the IBM Knowledge Catalog , enhancing data governance and consumption. Data Stewardship : Data stewards can utilize dynamic views for metadata enrichment, profiling, and data governance activities.

SQL 130

SQL Data Quality Data Governance Data Scientist 130

Data Science Dojo

SEPTEMBER 6, 2023

Once authenticated, authorization ensures that the individual is allowed access only to the areas they are authorized to enter. Data Governance: Setting the Rules D ata governance takes on the role of a regulatory framework, guiding the responsible management, utilization, and protection of your organization’s most valuable asset—data.

Data Warehouse 195

Data Warehouse Data Governance Data Quality ETL 195

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.

Data Quality 74

Data Quality Data Profiling Data Governance Analytics 74

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. What is data governance?

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. What is data governance?

Data Governance 70

Data Governance Data Analyst Data Quality Data Silos 70

Dataconomy

APRIL 21, 2023

In retail, complete and consistent data is necessary to understand customer behavior and optimize sales strategies. Without data fidelity, decision-makers cannot rely on data insights to make informed decisions. Poor data quality can result in wasted resources, inaccurate conclusions, and lost opportunities.

Data Quality 149

Data Quality Data Governance Data Visualization Power BI 149

Dataversity

NOVEMBER 22, 2022

The public was less concerned about securing their data assets and was only fascinated by the fact that the interconnected digital world would change their lives forever. The post Data Science and Privacy: Defending Sensitive Data in the Age of Analytics appeared first on DATAVERSITY.

Data Science 98

Data Science Analytics Analytics Big Data 98

Pickl AI

OCTOBER 10, 2023

In this blog, we are going to unfold the two key aspects of data management that is Data Observability and Data Quality. Data is the lifeblood of the digital age. Today, every organization tries to explore the significant aspects of data and its applications.

Data Observability 52

Data Observability Data Quality Data Governance Data Pipeline 52

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? Bias in data can result in unfair and discriminatory outcomes.

Data Quality 52

Data Quality Machine Learning Machine Learning Clean Data 52

Pickl AI

OCTOBER 19, 2023

Data quality plays a significant role in helping organizations strategize their policies that can keep them ahead of the crowd. Hence, companies need to adopt the right strategies that can help them filter the relevant data from the unwanted ones and get accurate and precise output.

Data Quality 52

Data Quality Data Governance Data Warehouse Machine Learning 52

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?

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

Alation

FEBRUARY 17, 2023

This past week, I had the pleasure of hosting Data Governance for Dummies author Jonathan Reichental for a fireside chat , along with Denise Swanson , Data Governance lead at Alation. Can you have proper data management without establishing a formal data governance program?

Data Governance 52

Data Governance Data Quality Data Analyst Data Pipeline 52

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.

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

AWS Machine Learning Blog

APRIL 3, 2025

Data governance challenges Maintaining consistent data governance across different systems is crucial but complex. The company aims to integrate additional data sources, including other mission-critical systems, into ODAP. The following diagram shows a basic layout of how the solution works.

AWS 79

AWS Data Governance Data Silos SQL 79

IBM Data Science in Practice

NOVEMBER 28, 2022

IBM Multicloud Data Integration helps organizations connect data from disparate sources, build data pipelines, remediate data issues, enrich data, and deliver integrated data to multicloud platforms where it can easily accessed by data consumers or built into a data product.

Data Pipeline 130

Data Pipeline Data Quality Data Preparation Data Governance 130

Dataversity

FEBRUARY 4, 2022

According to Gartner, 85% of Data Science projects fail (and are predicted to do so through 2022). I suspect the failure rates are even higher, as more and more organizations today are trying to utilize the power of data to improve their services or create new revenue streams.

Data Quality 52

Data Quality Data Science Data Scientist Data Governance 52

Data Science Dojo

JULY 6, 2023

These tools provide data engineers with the necessary capabilities to efficiently extract, transform, and load (ETL) data, build data pipelines, and prepare data for analysis and consumption by other applications. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

Data Engineer 195

Data Engineer Data Engineering Data Engineering Data Engineering 195

Data Science Dojo

OCTOBER 10, 2023

Generative AI and Data Storytelling (Virtual event | 27th September – 2023) A virtual event on generative AI and data storytelling. The event is hosted by Data Science Dojo and will be held on September 27, 2023. The speaker is Andrew Madson, a data analytics leader and educator.

AI 243

AI AI Data Observability Artificial Intelligence 243

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 […].

Data Governance 98

Data Governance Business Intelligence Business Intelligence Data Quality 98

Data Science Dojo

MARCH 24, 2023

Data Management: Effective data management is crucial for ML models to work well. This includes ensuring that data is properly labeled and processed, managing data quality, and ensuring that the right data is used for training and testing models.

Machine Learning 195

Machine Learning Machine Learning ML ML 195

Data Science Dojo

MARCH 24, 2023

Data Management: Effective data management is crucial for ML models to work well. This includes ensuring that data is properly labeled and processed, managing data quality, and ensuring that the right data is used for training and testing models.

Machine Learning 195

Machine Learning Machine Learning ML ML 195

Alation

DECEMBER 15, 2021

Yet high-volume collection makes keeping that foundation sound a challenge, as the amount of data collected by businesses is greater than ever before. An effective data governance strategy is critical for unlocking the full benefits of this information. Data governance requires a system.

Data Governance 52

Data Governance Data Quality Analytics Analytics 52

Dataversity

AUGUST 10, 2023

We’ve all generally heard that data quality issues can be catastrophic. But what does that look like for data teams, in terms of dollars and cents? And who is responsible for dealing with data quality issues?

Data Quality 52

Data Quality Data Engineer Data Engineering Data Engineering 52

Dataversity

JANUARY 26, 2022

The importance of data has increased multifold as we step into 2022, with an emphasis on active Data Management and Data Governance. Furthermore, thanks to the introduction of new technology and tools, we are now able to automate labor-intensive data and privacy operations.

Data Governance 52

Data Governance Data Quality Data Science 52

Dataconomy

APRIL 6, 2023

Another key benefit of data democratization is that it can help to improve data quality by making it easier for people to spot errors and inconsistencies in data. This can lead to better data governance practices and, ultimately, more accurate insights.

Data Governance 118

Data Governance Data Silos Data Analysis Data Analysis 118

Precisely

JANUARY 23, 2024

Data Governance Goes Mainstream To get the most from data analytics initiatives, organizations must proactively work to build data integrity. Doing so requires a sound data governance framework. As such, data governance is a key factor in determining how well organizations achieve compliance and trust.

Data Governance 69

Data Governance Data Quality Analytics Analytics 69

ODSC - Open Data Science

APRIL 28, 2023

These are critical steps in ensuring businesses can access the data they need for fast and confident decision-making. As much as data quality is critical for AI, AI is critical for ensuring data quality, and for reducing the time to prepare data with automation. Tendü received her Ph.D.

ML 98

ML ML Data Silos Data Quality 98

Data Science Dojo

AUGUST 24, 2023

MLOps facilitates automated testing mechanisms for ML models, which detects problems related to model accuracy, model drift, and data quality. Consider a scenario where a data science team without dedicated MLOps practices is developing an ML model for sales forecasting. Docker) or virtual environments (i.e.,

Machine Learning 195

Machine Learning Machine Learning ML ML 195

Data Science Connect

MARCH 22, 2023

Set up monitoring tools: Once you’ve identified your data sources, set up monitoring tools to keep track of your data. This could include data quality checks, alerts, and notifications. Establish data governance: Establish clear data governance policies to ensure that your data is accurate, complete, and accessible.

Data Observability 130

Data Observability Data Governance Analytics Analytics 130

Data Science Dojo

JANUARY 12, 2023

Data Lakes compared to Data Warehouses – two different approaches What a data lake is not also helps to define it. Additionally, unprocessed, raw data is pliable and suitable for machine learning. Consider them complimentary tools rather than competitors, as certain businesses may require both.

Data Lakes 221

Data Lakes Data Warehouse Hadoop Machine Learning 221

Precisely

APRIL 17, 2023

Data quality and consistency, for example, are essential prerequisites for trusted data-driven decisions. Privacy and security are increasingly under the spotlight, driving an increased focus on regulatory compliance and data governance. Data quality remains a top concern for many enterprises.

Data Governance 59

Data Governance Data Quality Data Science ML 59

The MLOps Blog

JUNE 27, 2023

With built-in components and integration with Google Cloud services, Vertex AI simplifies the end-to-end machine learning process, making it easier for data science teams to build and deploy models at scale. Metaflow Metaflow helps data scientists and machine learning engineers build, manage, and deploy data science projects.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Pickl AI

JULY 25, 2023

Together, data engineers, data scientists, and machine learning engineers form a cohesive team that drives innovation and success in data analytics and artificial intelligence. Their collective efforts are indispensable for organizations seeking to harness data’s full potential and achieve business growth.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52