Pickl AI

OCTOBER 19, 2023

Whether you are a business executive making critical choices, a scientist conducting groundbreaking research, or simply an individual seeking accurate information, data quality is a paramount concern. The Relevance of Data Quality Data quality refers to the accuracy, completeness, consistency, and reliability of data.

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Data Quality Data Governance Data Warehouse Machine Learning 52

DataRobot Blog

OCTOBER 9, 2017

2) Data Profiling : To profile data in Excel, users typically create filters and pivot tables – but problems arise when a column contains thousands of distinct values or when there are duplicates resulting from different spellings. 3) Data Governance and Trust: With Excel, there is no actual audit trail or data lineage.

Data Preparation 52

Data Preparation Data Profiling Data Governance Machine Learning 52

Alation

JANUARY 13, 2022

But make no mistake: A data catalog addresses many of the underlying needs of this self-serve data platform, including the need to empower users with self-serve discovery and exploration of data products. In this blog series, we’ll offer deep definitions of data fabric and data mesh, and the motivations for each. (We

Data Lakes 59

Data Lakes Data Governance Data Quality Data Warehouse 59

Pickl AI

OCTOBER 11, 2023

Data Observability and Data Quality are two key aspects of data management. The focus of this blog is going to be on Data Observability tools and their key framework. The growing landscape of technology has motivated organizations to adopt newer ways to harness the power of data.

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IBM Journey to AI blog

JANUARY 5, 2023

Efficiently adopt data platforms and new technologies for effective data management. Apply metadata to contextualize existing and new data to make it searchable and discoverable. Perform data profiling (the process of examining, analyzing and creating summaries of datasets).

Data Quality 52

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The MLOps Blog

JUNE 27, 2023

It sits between the data lake and cloud object storage, allowing you to version and control changes to data lakes at scale. LakeFS facilitates data reproducibility, collaboration, and data governance within the data lake environment. Share features across the organization.

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Pickl AI

AUGUST 30, 2024

Introduction It is a critical process in the digital landscape, enabling organisations to transfer data between systems, formats, or storage solutions. As businesses evolve, the need for efficient data management becomes paramount. Explore More: Cloud Migration: Strategy and Tools What is Data Migration?

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Alation

DECEMBER 7, 2021

Customers enjoy a holistic view of data quality metrics, descriptions, and dashboards, which surface where they need it most: at the point of consumption and analysis. Trust flags signal the trustworthiness of data, and data profiling helps users determine usability. Subscribe to Alation's Blog.

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phData

JUNE 26, 2023

Welcome to the latest installment of the phData Toolkit blog series! in this June episode of the blog. Data Source Tool Updates The data source tool has a number of use cases, as it has the ability to profile your data sources and take the resulting JSON to perform whatever action you want to take.

SQL 52

SQL Data Profiling Data Pipeline Data Governance 52

phData

AUGUST 17, 2023

By providing a centralized platform for workflow management, these tools enable data engineers to design, schedule, and optimize the flow of data, ensuring the right data is available at the right time for analysis, reporting, and decision-making. This enhances the reliability and resilience of the data pipeline.

Data Engineering 52

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Alation

DECEMBER 21, 2022

Early on, analysts used data catalogs to find and understand data more quickly. Increasingly, data catalogs now address a broad range of data intelligence solutions, including self-service analytics , data governance , privacy , and cloud transformation. Subscribe to Alation's Blog.

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Data Quality Data Warehouse Data Profiling Data Governance 52

Dataversity

DECEMBER 16, 2020

According to IDC, the size of the global datasphere is projected to reach 163 ZB by 2025, leading to the disparate data sources in legacy systems, new system deployments, and the creation of data lakes and data warehouses. Most organizations do not utilize the entirety of the data […].

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Data Warehouse Data Lakes Data Profiling Data Quality 69

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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Data Warehouse Business Intelligence Business Intelligence Data Profiling 59

Dataversity

APRIL 22, 2022

In today’s digital world, data is undoubtedly a valuable resource that has the power to transform businesses and industries. As the saying goes, “data is the new oil.” However, in order for data to be truly useful, it needs to be managed effectively.

Data Profiling 52

Data Profiling Data Quality Data Governance Artificial Intelligence 52

Alation

JULY 6, 2021

Common Data Governance Challenges. Every enterprise runs into data governance challenges eventually. Issues like data visibility, quality, and security are common and complex. Data governance is often introduced as a potential solution. And one enterprise alone can generate a world of data.

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Data Governance Data Quality Data Silos Data Profiling 52

Alation

AUGUST 26, 2021

It asks much larger questions, which flesh out an organization’s relationship with data: Why do we have data? Why keep data at all? Answering these questions can improve operational efficiencies and inform a number of data intelligence use cases, which include data governance, self-service analytics, and more.

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phData

SEPTEMBER 1, 2023

From the sheer volume of information to the complexity of data sources and the need for real-time insights, HCLS companies constantly need to adapt and overcome these challenges to stay ahead of the competition. In this blog, we’ll explore 10 pressing data analytics challenges and discuss how Sigma and Snowflake can help.

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