IBM Journey to AI blog

JANUARY 8, 2024

In modern enterprises, where operations leave a massive digital footprint, business events allow companies to become more adaptable and able to recognize and respond to opportunities or threats as they occur. Teams want more visibility and access to events so they can reuse and innovate on the work of others.

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Women in Big Data

MAY 23, 2025

The Women in Big Data Bay Area Lightning Talks are a must-attend for professionals seeking cutting-edge insights, technical deep dives, and real-world expertise from industry leaders. Our events foster inclusive discussionswelcoming men and women aliketo build a diverse, collaborative tech community.

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AWS Machine Learning Blog

MARCH 18, 2025

The LLM analyzes the text, identifying key information relevant to the clinical trial, such as patient symptoms, adverse events, medication adherence, and treatment responses. These insights can include: Potential adverse event detection and reporting. Identification of protocol deviations or non-compliance. No problem!

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Data Science Blog

JULY 23, 2023

It advocates decentralizing data ownership to domain-oriented teams. Each team becomes responsible for its Data Products , and a self-serve data infrastructure is established. This enables scalability, agility, and improved data quality while promoting data democratization.

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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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Precisely

FEBRUARY 14, 2023

Innovations like RPA may be the newest shiny objects, but their success is largely dependent on two things: the quality of the data that feeds automated processes, and the enrichment of this data to accelerate the automation process. If the data does validate the hail , the claim can be passed on to the next step in processing.

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Precisely

MAY 4, 2023

Read the Report TDWI Checklist Report: Succeeding with Data Observability This report discusses five best practices for using observability tools to monitor, manage, and optimize operational data pipelines. It provides strategic guidance for enterprise data leaders in defining the core metrics of data quality and pipeline health.

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Dataconomy

JUNE 10, 2025

Diagnostic analytics Diagnostic analytics explores historical data to explain the reasons behind events. Following these steps ensures the validity and usefulness of insights derived from data. Data governance Establishing compliance with data usage standards and organizational policies is crucial for ethical data handling.

Analytics 91

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Precisely

FEBRUARY 14, 2023

Innovations like RPA may be the newest shiny objects, but their success is largely dependent on two things: the quality of the data that feeds automated processes, and the enrichment of this data to accelerate the automation process. If the data does validate the hail , the claim can be passed on to the next step in processing.

Data Quality 52

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Dataversity

JANUARY 15, 2025

Theres nothing quite like gathering with data professionalsfriends old and new at a DATAVERSITY conference.Last months event was particularly special, combining the well-established Data Governance & Information Quality (DGIQ) East Conference with the inaugural AI Governance Conference (AIGov).Adding

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Pickl AI

OCTOBER 18, 2023

How to Scale Your Data Quality Operations with AI and ML: In the fast-paced digital landscape of today, data has become the cornerstone of success for organizations across the globe. Every day, companies generate and collect vast amounts of data, ranging from customer information to market trends.

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phData

OCTOBER 25, 2024

“Quality over Quantity” is a phrase we hear regularly in life, but when it comes to the world of data, we often fail to adhere to this rule. Data Quality Monitoring implements quality checks in operational data processes to ensure that the data meets pre-defined standards and business rules.

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Data Science Blog

JUNE 27, 2023

In this representation, there is a separate store for events within the speed layer and another store for data loaded during batch processing. The serving layer acts as a mediator, enabling subsequent applications to access the data. On the other hand, the real-time views provide immediate access to the most current data.

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IBM Journey to AI blog

NOVEMBER 21, 2023

Apache Kafka is a well-known open-source event store and stream processing platform and has grown to become the de facto standard for data streaming. A schema registry is essentially an agreement of the structure of your data within your Kafka environment. Provision an instance of Event Streams on IBM Cloud here.

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Data Science Dojo

OCTOBER 9, 2023

However, collecting and labeling real-world data can be costly, time-consuming, and inaccurate. Synthetic data offers a solution to these challenges. Scalability: Easily generate synthetic data for large-scale projects. Accuracy: Synthetic data can match real data quality.

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ODSC - Open Data Science

JUNE 10, 2025

By automating SQL generation, businesses can empower a broader range of users to access and analyze data directly. Why Data Quality and Freshness Matter Generative AI’s performance is tightly linked to the quality and timeliness of the data it consumes. Incorporate rigorous prompt testing to eliminate errors.

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Precisely

MARCH 18, 2025

There were many Gartner keynotes and analyst-led sessions that had titles like: Scale Data and Analytics on Your AI Journeys” What Everyone in D&A Needs to Know About (Generative) AI: The Foundations AI Governance: Design an Effective AI Governance Operating Model The advice offered during the event was relevant, valuable, and actionable.

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Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. That is still in flux and being worked out.

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Dataconomy

MAY 26, 2025

Understanding the data-driven philosophy Organizations excelling in business analytics view data as a vital asset and strive to leverage it for strategic competitive advantages. The effectiveness of business analytics heavily depends on data quality, expert analysts, and an organizational commitment to data-driven decision-making.

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Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. That is still in flux and being worked out.

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Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. That is still in flux and being worked out.

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Dataconomy

SEPTEMBER 4, 2023

Diagnostic analytics: Diagnostic analytics goes a step further by analyzing historical data to determine why certain events occurred. By understanding the “why” behind past events, organizations can make informed decisions to prevent or replicate them.

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Precisely

MARCH 3, 2025

Data quality and governance are critical. Without clean, governed data, automation efforts can be undermined, impacting your business outcomes and AI initiatives. Data and process automation used to be seen as luxury but those days are gone. The result?

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PyImageSearch

JANUARY 6, 2025

It stands out due to its unusually high or low value compared to the rest of the data, which can indicate that it’s an anomaly, error, or something noteworthy. measurement errors, data entry mistakes, or genuine but rare events). In quality control, an outlier could indicate a defect in a manufacturing process.

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Dataversity

JANUARY 26, 2024

As our reliance on data-intensive sectors like finance, healthcare, and the Internet of Things (IoT) grows, the question of trust becomes paramount.

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Flipboard

MAY 20, 2025

Enterprisesespecially in the insurance industryface increasing challenges in processing vast amounts of unstructured data from diverse formats, including PDFs, spreadsheets, images, videos, and audio files. These might include claims document packages, crash event videos, chat transcripts, or policy documents.

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Data Science Dojo

SEPTEMBER 6, 2023

Defining Data Ownership: Assigning Custodianship Like a castle with appointed caretakers, data governance designates data owners responsible for different datasets. Data ownership extends beyond mere possession—it involves accountability for data quality, accuracy, and appropriate use.

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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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Dataversity

APRIL 30, 2021

The goal of digital transformation remains the same as ever – to become more data-driven. We have learned how to gain a competitive advantage by capturing business events in data. Events are data snap-shots of complex activity sourced from the web, customer systems, ERP transactions, social media, […].

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Dataconomy

MARCH 5, 2025

Descriptive analytics is a fascinating area of data analytics that allows businesses to look back and glean insights from their historical data. By summarizing past events and performance metrics, organizations can understand trends, patterns, and behaviors that shape their decision-making processes.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

It helps organizations comply with regulations, manage risks, and maintain operational efficiency through robust model lifecycles and data quality management. Prepare the data to build your model training pipeline. Train your ML model with the prepared data and register the candidate model package version with training metrics.

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Dataconomy

APRIL 2, 2025

No model, however sophisticated, can account for the black swan events, regulatory changes, or exchange outages. Every quantitative team has to deal with issues relating to data quality, latency and model overfitting. There is historical evidence of post-halving cycles that supports these predictions.

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Pickl AI

FEBRUARY 17, 2025

Summary: Machine Learning’s key features include automation, which reduces human involvement, and scalability, which handles massive data. It uses predictive modelling to forecast future events and adaptiveness to improve with new data, plus generalization to analyse fresh data.

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AWS Machine Learning Blog

FEBRUARY 27, 2024

In this case, we are developing a forecasting model, so there are two main steps to complete: Train the model to make predictions using historical data. Apply the trained model to make predictions of future events. Workflow A corresponds to preprocessing, data quality and feature attribution drift checks, inference, and postprocessing.

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ODSC - Open Data Science

DECEMBER 5, 2023

You can see our photos from the event here , and be sure to follow our YouTube for virtual highlights from the conference as well. Over in San Francisco, we had a keynote for each day of the event. Other Events Aside from networking events and all of our sessions, we had a few other special events. What’s next?

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Data Science Dojo

MARCH 18, 2024

Yet, despite these impressive capabilities, their limitations became more apparent when tasked with providing up-to-date information on global events or expert knowledge in specialized fields. The model might offer generic advice based on its training data but lacks depth or specificity – and, most importantly, accuracy.

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Women in Big Data

APRIL 3, 2025

Key Takeaways from the Event Generative AI moves from POC to industrialization : Financial sector companies are now deploying generative AI solutions at scale, with a focus on security, ethics, and ROI.

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