Iguazio

FEBRUARY 20, 2024

To learn more, watch the webinar “Implementing Gen AI for Financial Services” with Larry Lerner, Partner & Global Lead - Banking and Securities Analytics, McKinsey & Company, and Yaron Haviv, Co-founder and CTO, Iguazio (acquired by McKinsey), which this blog post is based on. View the entire webinar here. Read more here.

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Iguazio

JULY 22, 2024

The integrated solution allows customers to streamline data processing and storage, ensuring Gen AI applications reach production while eliminating risks, improving performance and enhancing governance. Iguazio capabilities: Structured and unstructured data pipelines for processing, versioning and loading documents.

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Alation

JUNE 14, 2023

Every organization wants to better serve its customers, and that goal is often achieved through data. Data Pipeline Capabilities This team’s scope is massive because the data pipelines are huge and there are many different capabilities embedded in them. You don’t have to write ETL jobs.” Invest in automation.

Data Pipeline 52

Data Pipeline ETL Data Warehouse SQL 52

IBM Journey to AI blog

NOVEMBER 3, 2023

.” This user interface not only brings Apache Flink to anyone that can add business value, but it also allows for experimentation that has the potential to drive innovation speed up your data analytics and data pipelines. Hungry for more?

Apache Kafka 79

Apache Kafka Data Warehouse Data Pipeline Big Data 79

Precisely

SEPTEMBER 30, 2024

Here are five data quality best practices which business leaders should focus. Think holistically: Address the entire data pipeline Data quality should not simply be focused on finding and fixing existing problems within static data. Waiting until later risks sending a bogus “lead” to inside sales for follow up.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

ODSC - Open Data Science

JANUARY 28, 2025

In a recent webinar, AI Mastery 2025: Skills to Stay Ahead in the Next Wave, hosted by Sheamus McGovern, founder of ODSC and a venture partner at Cortical Ventures, shared invaluable insights into the evolving AI landscape. LLM Engineers: With job postings far exceeding the current talent pool, this role has become one of the hottest inAI.

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AI AI Machine Learning Machine Learning 40

Precisely

APRIL 6, 2023

In a recent webinar hosted by Fintech Nexus, Doug Lopp, CTO of Bend by FNBO, remarked on the role of technology in today’s financial services organizations: “Business and technology are starting to align much more closely than they ever have before, to the point where they are indistinguishable. Real-time data is the goal.

Data Quality 52

Data Quality Data Pipeline Analytics Analytics 52

ODSC - Open Data Science

MAY 10, 2023

Many mistakenly equate tabular data with business intelligence rather than AI, leading to a dismissive attitude toward its sophistication. Standard data science practices could also be contributing to this issue. With all the attention on generative AI, tabular data isn’t getting the attention it deserves.

Data Scientist 87

Data Scientist Data Science Deep Learning Deep Learning 87

Alation

DECEMBER 23, 2021

Now, everyone can see the data… even Dancer, who’s fighting his way off the naughty list after spiking the reindeer trough with eggnog in the ‘80s. Get the most out of their Snowflake data cloud. Did anyone else catch Frizzle and Sparkle on our joint webinars this quarter? Boost collective data literacy and showcase experts.

Data Governance 59

Data Governance Data Pipeline Tableau Big Data 59

Tableau

DECEMBER 7, 2022

Every company today is being asked to do more with less, and leaders need access to fresh, trusted KPIs and data-driven insights to manage their businesses, keep ahead of the competition, and provide unparalleled customer experiences. But good data—and actionable insights—are hard to get. What is Salesforce Data Cloud for Tableau?

Tableau 55

Tableau Data Warehouse Data Pipeline Data Visualization 55

Snorkel AI

JULY 3, 2023

As the algorithms we use have gotten more robust and we have increased our compute power through new technologies, we haven’t made nearly as much progress on the data part of our jobs. Because of this, I’m always looking for ways to automate and improve our data pipelines. So why should we use data pipelines?

Exploratory Data Analysis 52

Exploratory Data Analysis Data Pipeline Data Scientist Machine Learning 52

Alation

FEBRUARY 17, 2023

Data from an ERP or MDM system could come in as raw, with technical names that match the source, and have some limited data definitions but no data quality aspects. These reports (combined with updates to the data governance roadmap, and your progress narrative) tell a great story. Curious to hear from the author?

Data Governance 52

Data Governance Data Quality Data Analyst Data Pipeline 52

Pickl AI

JULY 3, 2023

Participate in webinars, attend conferences, and join relevant professional communities. Build a portfolio: Develop a portfolio of BI projects that showcase your skills and demonstrate your ability to deliver actionable insights through effective data visualization and reporting.

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

Snorkel AI

JUNE 22, 2023

But a lot of what we’re talking about here is trying to build data pipelines that are going to run. Look at our events page to sign up for research webinars, product overviews, and case studies. The post McKinsey QuantumBlack on automating data quality remediation with AI appeared first on Snorkel AI.

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Data Quality ML ML AI 52

Pickl AI

SEPTEMBER 5, 2024

This section explores popular software and frameworks for Data Analysis and modelling is designed to cater to the diverse needs of Data Scientists: Azure Data Factory This cloud-based data integration service enables the creation of data-driven workflows for orchestrating and automating data movement and transformation.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

Iguazio

OCTOBER 20, 2024

For more details, watch the webinar this blog post is based on. The webinar hosts Eli Stein, Partner and Modern Marketing Capabilities Leader from McKinsey, Ze’ev Rispler, ML Engineer, from Iguazio (acquired by McKinsey), and myself. Watch the entire webinar here.

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AI AI Database Data Wrangling 96

Data Science Dojo

APRIL 3, 2025

The partnership between Databricks and Gencore AI enables enterprises to develop AI applications with robust security measures, optimized data pipelines, and comprehensive governance. Optimized Data Pipelines for AI Readiness AI models are only as good as the data they process.

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AI AI Data Pipeline Data Preparation 195

Iguazio

MARCH 20, 2025

To see the complete conversation and dive into their insights, watch the webinar here. See the webinar for more Gartner trends. Quality, Scalability and Continuous Delivery Implementing modularity with LLM, data, and API abstractions to ensure flexibility Implementing tests for models, prompts, application logic, etc.

AI 59

AI AI Data Pipeline Data Scientist 59

Flipboard

JUNE 16, 2025

Must-Have Skills for Data Engineers: Cloud Platforms : Expertise in AWS, Azure, and Google Cloud Platform (GCP) is vital for managing and deploying cloud-based data infrastructure. Database Management : It is crucial to have knowledge of both relational (e.g., MySQL, PostgreSQL) and non-relational (e.g., MongoDB, Cassandra) databases.

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Python AWS Machine Learning Machine Learning 50