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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Alation

JANUARY 20, 2022

Several weeks ago (prior to the Omicron wave), I got to attend my first conference in roughly two years: Dataversity’s Data Quality and Information Quality Conference. Ryan Doupe, Chief Data Officer of American Fidelity, held a thought-provoking session that resonated with me. Step 2: Data Definitions.

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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. What is Data Observability?

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Smart Data Collective

APRIL 20, 2022

Data entry errors will gradually be reduced by these technologies, and operators will be able to fix the problems as soon as they become aware of them. Make Data Profiling Available. To ensure that the data in the network is accurate, data profiling is a typical procedure.

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Precisely

JUNE 26, 2023

Successful organizations also developed intentional strategies for improving and maintaining data quality at scale using automated tools. Only 46% of respondents rate their data quality as “high” or “very high.” Only 46% of respondents rate their data quality as “high” or “very high.” The biggest surprise?

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Precisely

SEPTEMBER 11, 2023

It provides a unique ability to automate or accelerate user tasks, resulting in benefits like: improved efficiency greater productivity reduced dependence on manual labor Let’s look at AI-enabled data quality solutions as an example. Problem: “We’re unsure about the quality of our existing data and how to improve it!”

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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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Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

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Heartbeat

JUNE 12, 2023

This monitoring requires robust data management and processing infrastructure. Data Velocity: High-velocity data streams can quickly overwhelm monitoring systems, leading to latency and performance issues. Data profiling can help identify issues, such as data anomalies or inconsistencies.

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Alation

DECEMBER 21, 2022

Master Data Management (MDM) and data catalog growth are accelerating because organizations must integrate more systems, comply with privacy regulations, and address data quality concerns. What Is Master Data Management (MDM)? Implementing a data catalog first will make MDM more successful.

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Alation

SEPTEMBER 7, 2021

In the next section, let’s take a deeper look into how these key attributes help data scientists and analysts make faster, more informed decisions, while supporting stewards in their quest to scale governance policies on the Data Cloud easily. Find Trusted Data. Verifying quality is time consuming.

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Dataconomy

JULY 28, 2023

How to become a data scientist Data transformation also plays a crucial role in dealing with varying scales of features, enabling algorithms to treat each feature equally during analysis Noise reduction As part of data preprocessing, reducing noise is vital for enhancing data quality.

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Snorkel AI

OCTOBER 4, 2023

Data scientists can train large language models (LLMs) and generative AI like GPT-3.5 to generate natural language reports from tabular data that help human agents easily interpret complex data profiles on potential borrowers. Improve the accuracy of credit scoring predictions.

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Snorkel AI

OCTOBER 4, 2023

Data scientists can train large language models (LLMs) and generative AI like GPT-3.5 to generate natural language reports from tabular data that help human agents easily interpret complex data profiles on potential borrowers. Improve the accuracy of credit scoring predictions.

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Alation

DECEMBER 7, 2021

Alation and Bigeye have partnered to bring data observability and data quality monitoring into the data catalog. Read to learn how our newly combined capabilities put more trustworthy, quality data into the hands of those who are best equipped to leverage it. trillion each year due to poor data quality.

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Pickl AI

JULY 19, 2023

By maintaining clean and reliable data, businesses can avoid costly mistakes, enhance operational efficiency, and gain a competitive edge in their respective industries. Best Data Hygiene Tools & Software Trifacta Wrangler Pros: User-friendly interface with drag-and-drop functionality. Provides real-time data monitoring and alerts.

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The MLOps Blog

MARCH 15, 2023

Scalability : A data pipeline is designed to handle large volumes of data, making it possible to process and analyze data in real-time, even as the data grows. Data quality : A data pipeline can help improve the quality of data by automating the process of cleaning and transforming the data.

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phData

DECEMBER 29, 2022

This automation includes things like SQL translation during a data platform migration (SQLMorph), making changes to your Snowflake information architecture (Tram), and checking for parity and data quality between platforms (Data Source Automation). Let’s dive in and take a deeper look at these.

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Snorkel AI

MAY 12, 2023

Kishore will then double click into some of the opportunities we find here at Capital One, and Bayan will finish us off with a lean into one of our open-source solutions that really is an important contribution to our data-centric AI community. One of these is a library that we open-sourced a little while back called the Data Profiler.

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Snorkel AI

MAY 12, 2023

Kishore will then double click into some of the opportunities we find here at Capital One, and Bayan will finish us off with a lean into one of our open-source solutions that really is an important contribution to our data-centric AI community. One of these is a library that we open-sourced a little while back called the Data Profiler.

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The MLOps Blog

JUNE 27, 2023

Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Data monitoring tools help monitor the quality of the data.

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Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data Ensuring data quality and integrity Data quality and integrity are essential for accurate data analysis. Data engineers are responsible for ensuring that the data collected is accurate, consistent, and reliable.

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Dataversity

DECEMBER 7, 2020

Data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations who seek to empower more and better data-driven decisions and actions throughout their enterprises. These groups want to expand their user base for data discovery, BI, and analytics so that their business […].

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phData

AUGUST 17, 2023

This can significantly improve processing time and overall efficiency, enabling faster data transformation and analysis. Data Quality Management Orchestration tools can be utilized to incorporate data quality checks and validations into data pipelines.

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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.

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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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ODSC - Open Data Science

FEBRUARY 24, 2023

Data Quality Now that you’ve learned more about your data and cleaned it up, it’s time to ensure the quality of your data is up to par. With these data exploration tools, you can determine if your data is accurate, consistent, and reliable.

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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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Dataversity

JANUARY 11, 2021

In Part 1 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 user base for […].

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Smart Data Collective

SEPTEMBER 21, 2021

The data fabric solution must also embrace and adapt itself to new emerging technologies such as docker, Kubernetesinserverless computing, etc. Data quality and governance. Data fabric solutions must integrate data quality into each step of the data management process right from the initial stages.

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The MLOps Blog

MAY 17, 2023

Here are some specific reasons why they are important: Data Integration: Organizations can integrate data from various sources using ETL pipelines. This provides data scientists with a unified view of the data and helps them decide how the model should be trained, values for hyperparameters, etc.

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Alation

JANUARY 13, 2022

In fact, data intelligence technologies support building a data fabric and realizing a data mesh. Let’s turn our attention now to data mesh. What Is a Data Mesh? Responsibilities are distributed to the people who are closest to the data.

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phData

SEPTEMBER 1, 2023

By combining data from disparate systems, HCLS companies can perform better data analysis and make more informed decisions. See how phData created a solution for ingesting and interpreting HL7 data 4. Data Quality Inaccurate data can have negative impacts on patient interactions or loss of productivity for the business.

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Alation

JULY 6, 2021

Automated governance tracks data lineage so users can see data’s origin and transformation. Auto-tracked metrics guide governance efforts, based on insights around data quality and profiling. This empowers leaders to see and refine human processes around data. No Data Leadership. Data Quality.

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Alation

AUGUST 26, 2021

As lakes of data become oceans, locating that which is trustworthy and reliable grows more difficult — and important. Indeed, as businesses attempt to scale AI and BI programs, small issues around data quality can transmogrify into massive challenges. Data quality. Data governance. Data profiling.

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