Austin Senseman

In this #RHSummit analysis, #theCUBE's Rebecca M. Knight and Rob Strechay discuss Red Hat’s use cases for regular people—customer service representatives, non-data scientists, and accountants. https://lnkd.in/gKMiR85W “The use case is about taking your data, using InstructLab, #RHEL AI, and running it on #OpenShift AI to help a customer service agent provide a better customer experience to that end user who calls in and has a question. They can not only find the answer quickly, but they don't get hallucinations, shares Strechay. “They are also doing it in the style and the spirit. That's bringing your personalized jargon, the way in which your company approaches problems and any little problem that a customer might be having to deal with a customer service representative way on up to the boardroom,” adds Knight. 📰 More: https://lnkd.in/gKMiR85W #GenAI

1

Another great post from Melinda Roy on discovering that data governance is already happening at your institution, just in less formalized ways. This article describes how you can match data governance roles to existing higher ed roles. #highereducation #datagovernance #irwatercooler educause

2

Discover the power of Databricks SQL and Dashboards with guidance from Andrew McQueen and Tyler Faulkner of Xorbix at our "Exploring Data Warehousing" session. 📅 Join the Wisconsin Databricks User Group on September 12, 2024, from 5:30 pm to 7:30 pm. Learn more and register: https://lnkd.in/dXrT3KmX Elevate your knowledge and network with fellow data professionals. #DataWarehousing #Databricks #AI #DataScience #Networking

7

Discover the power of Databricks SQL and Dashboards with guidance from Andrew McQueen and Tyler Faulkner of Xorbix at our "Exploring Data Warehousing" session. 📅 Join the Wisconsin Databricks User Group on September 12, 2024, from 5:30 pm to 7:30 pm. Learn more and register: https://lnkd.in/dXrT3KmX Elevate your knowledge and network with fellow data professionals. #DataWarehousing #Databricks #AI #DataScience #Networking

5

👨‍💻 "We'll just pull from the Snowflake private data share and put it into our own Snowflake instance and it should be fine." Does this sound familiar to you? If your #investmentmanagement firm is pulling data from a third party's Snowflake instance into your own, there's a good chance that data quality checks are being neglected. Without the right integrity and consistency checks of the data, operational risks will creep in. With our FenDQ engine, clients working with Snowflake can now use our no-code data quality platform to run automated, customised data quality and business validation checks on incoming data in a cost effective manner. Interested to find out more? Send us an email at [email protected] or [email protected] #dataqualityplatform #dataquality #snowflake #snowflakeintegration

14

Cross-industry cloud database technology Snowflake can really benefit from a layer of investment management expertise. Speak to us today to learn how to best leverage this great technology. #investmentmanagement #datamanagement #Snowflake #dqchecks #dataquality

2

Critical dbt models are those that you know have a significant business value, they're the fragile break points in the pipeline, and you know you’re gonna get a call if something’s not right 🕣☎️🥱 Check these models for EVERY PR, regardless of the work being done. You don’t want: ❌ lost rows ❌ unintentional schema change ❌ historical metrics change These checks need to be automated. Don't rely on development-time ad-hoc checks for these models. Preset Checks in Recce automate the process of checking these models in CI. If there’s a data mismatch after opening a PR, the model will be listed in the Recce CI Summary. Open Recce in Review Mode to see exactly what happened! Get Critical model coverage and stop clicking merge and hoping for the best. #dbt #dataops #dataengineering #criticaldata

7

1 Comment

An interesting study from Bill Schmarzo and Mark Stouse in Data Science Central "We have been vocal about my belief that organizations focusing on GenAI-driven productivity improvements rather than GenAI-driven innovation improvements are missing the bigger prize. GenAI tools can create value for an organization, but that increase in value is inconsistent. On one hand, GenAI tools can improve the productivity (efficiency) of below-average workers. On the other hand, they can significantly boost the innovation (effectiveness) of top-performing workers who better understand critical value-creation concepts such as data science, design thinking, and economics." #ai #genai #automation #productivity #innovation #teckedin https://lnkd.in/g7kgMnxf

8

1 Comment

Minor update to my sworn graph trends dashboard, you can now do query parameters to pull up a specific agency + population band. Here is Fayetteville https://lnkd.in/emXMYyTQ If LinkedIn eats the url, it is `graphs/sworn?ori=AR0720100&lowpop=50000&highpop=200000`. You can see Fayetteville is lagging behind in hiring female officers relative to the US average, but has been increasing since 2015. It is on the lower end for sworn rates (comparing to cities in the 50k to 200k range), but civilian rates are right at the 50% percentile. #policing #javascript #30x30

5

Are you a data leader looking to transform your organization’s #datagovernance practices? Join us for an exclusive 30-minute webinar designed specifically for State, Local and Education (#SLED) agencies. Discover how to implement data governance with #erwin Data Intelligence (DI) and Sandhill’s COMPASS DG Framework. Don't miss this, reserve your spot now. https://bit.ly/45UBAP8 #DataLeadership #DataStrategy

3

A common question asked by new founders of data analytics agencies is around how to price projects. In my latest video I explain 2 common approaches you can use to price your projects. https://lnkd.in/eSdMrhKn #dataanalytics #pricing #projects #dataanalysis #dataanalyst #agency

40

3 Comments

How my machine learning models feel after I feed them Big Data. Check out all the hit new findings and business intelligence savvy in this data driven blog article here. Brought to you by Data Mining Mike the best AI expert in Spokane Washington 2024. https://lnkd.in/gveMh3hZ

2

If you're looking for a new dataset to use in data projects / demos, check out the Iowa Liquor Sales data. It has a few things missing from most public datasets: * It's granular * It's pretty big (29m rows) * It's over a long time period (starts in 2012) * Has a good mix of numeric, categorical, and geographic data (though confined to Iowa) https://lnkd.in/eJNXREwn

22

3 Comments

🤔 Are you feeling overwhelmed by the size and complexity of your data sets in Power BI? Our latest article offers tips for dealing with large datasets so you can improve performance and efficiency. 🚀 Learn about: Strategies to combat data model limitations. Best practices like aggregated tables and model simplification. 👉 Learn how to make your Big Data operations more efficient for better results: https://lnkd.in/g3Jun_n7 #BigData #PowerBI #DataChallenges #BusinessIntelligence

7

From the genesis of the ❄ Snowflake Data Cloud to the creation of its revolutionary Marketplace, Matthew J. Glickman and Justin Langseth have been at the forefront of data innovation. Eventually, this led to building upon the very platform they had helped create, pushing the boundaries of what's possible in the AI Data Cloud. As we enter the next frontier of AI, the focus shifts to even more groundbreaking developments. Julian Forero delves deep into 🤖 Genesis Computing, uncovering the intricacies of true autonomous AI Co-workers and how Snowflake enables them on the AI Data Cloud. These AI Co-workers work alongside human counterparts & can complete tasks autonomously. This exploration highlights the evolution of data technology while also offering a glimpse into the reality of true autonomous agentic workflows; revealing AI's true potential to transform the landscape of enterprise production AI. Watch The Full Interview👉 https://lnkd.in/e5BDfgBN

42

"This book could be helpful for data professionals with no business background or are newer to the business side of things." In Jennifer L.'s latest review, she dives into Business 101 for the Data Professional by Jordan Morrow. https://lnkd.in/eDD8rjFZ #DataViz #DataVisualization #BookReview #BusinessData

18

2 Comments

Businesses caught between a more chaotic environment on one hand and messier data on the other often find themselves prioritizing data quality and planning tools. But there's a better way: In this article, Spaulding Ridge's Mei Liu and Michael Guzman explore how to balance planning and data, giving your organizations better strategic insights and getting you ready for AI. https://lnkd.in/gPUhVATf #SpauldingRidge #AIEfficiency #ROIResults

30

Semantic modeling and knowledge graphs are not "nice to haves." They bring context and meaning to information.

9

1 Comment