Data Related Topics 
Start Data Engineering
JUNE 14, 2024
Run Data Pipelines 2.1. Introduction Whether you are new to data engineering or have been in the data field for a few years, one of the most challenging parts of learning new frameworks is setting them up! Introduction 2. Run on codespaces 2.2. Run locally 3. Projects 3.1. Projects from least to most complex 3.2. Conclusion 1.
Christophe Blefari
JULY 26, 2024
Tallinn ( credits ) Dear members, it's Summer Data News, the only news you can consume by the pool, the beach or at the office—if you're not lucky. Joe is a great speaker, he wrote Fundamentals of Data Engineering , which is one of the bibles in data engineering and I can't wait to hear him at Forward Data.
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Confessions of a Data Guy
JULY 24, 2024
We all keep hearing about Arrow this and Arrow that … seems every new tool built today for Data Engineering seems to be at least partly based on Arrow’s in-memory format. So, […] The post PyArrow vs Polars (vs DuckDB) for Data Pipelines. appeared first on Confessions of a Data Guy.
Seattle Data Guy
JULY 2, 2024
Running a successful data team is hard. Data teams are expected to juggle a combination of ad-hoc requests, big bet projects, migrations, etc. All while keeping up with the latest changes in technology.
Speaker: Aindra Misra, Sr. Staff Product Manager of Data & AI at BILL (Previously PM Lead at Twitter/X)
Embark on a transformation journey into the heart of the data ecosystem! This webinar is your gateway to a deeper comprehension of the foundations that drive the data industry and will equip you with the knowledge needed to navigate the evolving landscape. Delve into the diverse use cases where data analytics plays a pivotal role.
Start Data Engineering
JULY 16, 2024
Data Quality(DQ) checks are run as part of your pipeline 2.1. Ensure your consumers don’t get incorrect data with output DQ checks 2.2. Introduction 2. Catch upstream issues quickly with input DQ checks 2.3. Waiting a long time to run output DQ checks? Save time & money with mid-pipeline DQ checks.
Christophe Blefari
MARCH 15, 2024
Saying mainly that " Sora is a tool to extend creativity " Last point Mira has been mocked and criticised online because as a CTO she wasn't able to say on which public / licensed data Sora has been trained on. Pandera, a data validation library for dataframes, now supports Polars.
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Adding high-quality entity resolution capabilities to enterprise applications, services, data fabrics or data pipelines can be daunting and expensive. Organizations often invest millions of dollars and years of effort to achieve subpar results.
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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. The quick-to-deploy Senzing® entity resolution API enables graph database users to gain insights from their data they couldn’t see before.
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Storytelling is more than just data visualization. Storytelling provides an organized approach for conveying data insights through visuals and narrative. Data-driven storytelling could be used to influence user actions, and ensure they understand what data matters the most.
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Every data-driven project calls for a review of your data architecture—and that includes embedded analytics. Before you add new dashboards and reports to your application, you need to evaluate your data architecture with analytics in mind. Expert guidelines for a high-performance, analytics-ready modern data architecture.
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The complexity of financial data, the need for real-time insight, and the demand for user-friendly visualizations can seem daunting when it comes to analytics - but there is an easier way. Together, we can overcome these hurdles and empower your users with the data they need to drive success.
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Organizational data literacy is regularly addressed, but it’s uncommon for product managers to consider users’ data literacy levels when building products. Product managers need to research and recognize their end users' data literacy when building an application with analytic features.
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The world of data analytics is changing fast as organizations look to gain competitive advantages through the application of timely data.
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In the fast-moving manufacturing sector, delivering mission-critical data insights to empower your end users or customers can be a challenge. Traditional BI tools can be cumbersome and difficult to integrate - but it doesn't have to be this way.
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