Data Science Dojo

NOVEMBER 15, 2023

Artificial intelligence (AI) is rapidly transforming our world, and AI conferences are a great way to stay up to date on the latest trends and developments in this exciting field. The 2023 edition of Big Data & AI Toronto will be held on October 18-19, 2023 at the Metro Toronto Convention Centre.

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IBM Journey to AI blog

AUGUST 23, 2023

The recent success of artificial intelligence based large language models has pushed the market to think more ambitiously about how AI could transform many enterprise processes. However, consumers and regulators have also become increasingly concerned with the safety of both their data and the AI models themselves.

Data Governance 66

Data Governance AI AI Artificial Intelligence 66

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. What is Data Observability and its Significance?

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Data Observability Data Quality Data Governance Data Pipeline 52

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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Data Observability Data Quality Data Pipeline Data Governance 52

Precisely

MAY 4, 2023

It includes streaming data from smart devices and IoT sensors, mobile trace data, and more. Data is the fuel that feeds digital transformation. But with all that data, there are new challenges that may require consider your data observability strategy. Is your data governance structure up to the task?

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Dataversity

APRIL 25, 2022

If data processes are not at peak performance and efficiency, businesses are just collecting massive stores of data for no reason. Data without insight is useless, and the energy spent collecting it, is wasted. The post Solving Three Data Problems with Data Observability appeared first on DATAVERSITY.

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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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AI AI Data Governance Data Pipeline 103

ODSC - Open Data Science

JANUARY 9, 2024

This will become more important as the volume of this data grows in scale. Data Governance Data governance is the process of managing data to ensure its quality, accuracy, and security. Data governance is becoming increasingly important as organizations become more reliant on data.

Data Engineering 97

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Precisely

MARCH 7, 2024

Insurance industry leaders are just beginning to understand the value that generative AI can bring to the claims management process. Yet experts warn that without proactive attention to data quality and data governance, AI projects could face considerable roadblocks.

AI 72

AI AI Data Governance Data Quality 72

IBM Data Science in Practice

NOVEMBER 28, 2022

Customer 360 : create a comprehensive view of client Multicloud data integration : integrate data across any hybrid and multicloud landscapes Data governance and privacy : automate to manage data trust, protection and compliance MLOps and trustworthy AI : enable an end-to-end AI workflow infused with data governance and privacy Data observability : (..)

Data Pipeline 130

Data Pipeline Data Quality Data Preparation Data Governance 130

IBM Journey to AI blog

FEBRUARY 26, 2024

The financial services industry has been in the process of modernizing its data governance for more than a decade. But as we inch closer to global economic downturn, the need for top-notch governance has become increasingly urgent. That’s why data pipeline observability is so important.

Data Pipeline 112

Data Pipeline Data Engineering Data Engineer Data Engineering 112

Precisely

JUNE 6, 2023

Salam noted that organizations are offloading computational horsepower and data from on-premises infrastructure to the cloud. This provides developers, engineers, data scientists and leaders with the opportunity to more easily experiment with new data practices such as zero-ETL or technologies like AI/ML.

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Precisely

OCTOBER 16, 2023

Big data analytics, IoT, AI, and machine learning are revolutionizing the way businesses create value and competitive advantage. BI platforms and data warehouses have been replaced by modern data lakes and cloud analytics solutions. In a connected mainframe/cloud environment, data is often diverse and fragmented.

Analytics 72

Analytics Analytics Big Data Analytics Big Data Analytics 72

Precisely

SEPTEMBER 11, 2023

Artificial intelligence (AI) has many applications, ranging from software products to appliances to cars and everything in between. AI has already made significant advancements in software – with even more exciting and promising developments ahead. So, What Does This All Mean for Precisely?

Data Quality 52

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IBM Journey to AI blog

JULY 3, 2024

By 2026, over 80% of enterprises will deploy AI APIs or generative AI applications. AI models and the data on which they’re trained and fine-tuned can elevate applications from generic to impactful, offering tangible value to customers and businesses. Data is exploding, both in volume and in variety.

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Precisely

JULY 18, 2024

Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata. As data grows exponentially, so do the complexities of managing and leveraging it to fuel AI and analytics.

Data Lakes 52

Data Lakes Data Warehouse Data Governance Machine Learning 52

IBM Journey to AI blog

DECEMBER 16, 2022

And because data assets within the catalog have quality scores and social recommendations, Alex has greater trust and confidence in the data she’s using for her decision-making recommendations. This is especially helpful when handling massive amounts of big data. Protected and compliant data.

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Precisely

MAY 31, 2023

Data Integrity Processes Run Where Data Lives Traditional data management solutions have required that data be brought to where the tools run. As a result, organizations have had to bring copies of their data to the tools – one copy for data quality, one copy for data governance, and so on.

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Precisely

OCTOBER 10, 2024

Organizations are evaluating modern data management architectures that will support wider data democratization. Why data democratization matters First and foremost, data democratization is about empowering employees to access the data that informs better business decisions. Read Data democracy: Why now?

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Data Quality Data Governance Analytics Analytics 52

Precisely

FEBRUARY 9, 2024

In 2023, organizations dealt with more data than ever and witnessed a surge in demand for artificial intelligence use cases – particularly driven by generative AI. They relied on their data as a critical factor to guide their businesses to agility and success.

Data Quality 69

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Precisely

OCTOBER 12, 2023

When we look by the numbers at the trends influencing data strategies, the survey says that organizations are … increasing flexibility, efficiency, and productivity while lowering costs through cloud adoption (57%) and digital transformation (43%) focusing on technologies that will help them manage resource shortages. Intelligence.

Data Quality 64

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IBM Journey to AI blog

JULY 13, 2023

This is the practice of creating, updating and consistently enforcing the processes, rules and standards that prevent errors, data loss, data corruption, mishandling of sensitive or regulated data, and data breaches.

Data Quality 74

Data Quality Data Profiling Data Governance Machine Learning 74

DagsHub

AUGUST 23, 2024

We already know that a data quality framework is basically a set of processes for validating, cleaning, transforming, and monitoring data. Data Governance Data governance is the foundation of any data quality framework. It primarily caters to large organizations with complex data environments.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

The MLOps Blog

JUNE 27, 2023

With Azure Machine Learning, data scientists can leverage pre-built models, automate machine learning tasks, and seamlessly integrate with other Azure services, making it an efficient and scalable solution for machine learning projects in the cloud. Might be useful Unlike manual, homegrown, or open-source solutions, neptune.ai

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Pickl AI

JULY 24, 2024

Bias Systematic errors introduced into the data due to collection methods, sampling techniques, or societal biases. Bias in data can result in unfair and discriminatory outcomes. Read More: Data Observability vs Data Quality Data Cleaning and Preprocessing Techniques This is a critical step in preparing data for analysis.

Data Quality 52

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Precisely

JUNE 5, 2023

The Data Quality service of the Precisely Data Integrity Suite can help – not only does it ensure data is complete, deduplicated, properly formatted, and standardized, but it also uses AI-based intelligence to make swift recommendations for areas in need of remediation. Addresses are often culprits here.

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Precisely

APRIL 15, 2025

Key Takeaways: Observability is essential for trusted AI Yet most organizations lack the structured programs, tools, and cross-team collaboration needed to make it effective. organizations show significantly higher observability maturity, trust in AI outputs, and use of diverse data types compared to Europe.

Data Observability 69

Data Observability Data Quality Data Pipeline AI 69

Precisely

FEBRUARY 28, 2025

The journey to trusting your data can be challenging, but you can more easily and effectively build data integrity when the core capabilities you need work together. Data integrity continues to grow in importance, especially if you aim to use your data for AI, automation, and other critical business initiatives.

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