LinkedIn

Creating online technology courses for the LinkedIn Learning data science library. Developed and recorded courses on Microsoft Power BI, Copilot, AWS QuickSight, Excel, R, and Python.

LinkedIn Learning Instructor

Helen Data Design

Interested in how to make data analytics and visualization a large scalable solution to understanding more about your business? I do Microsoft Power BI and AWS freelance consulting and training sessions on all parts of the technology, including queries, ETL frameworks, DAX calculations and modeling, and visualizations.

Founder and Principal

Rice University

Technology lead for Python for Business Analytics (MGMT 665) course for MBA students at the Jones Graduate School of Business

Lecturer in Management

Founderz

Developed and presented content in the Power BI-focused chapter in their new course: Online Master in AI and Innovation, created in collaboration with Microsoft.

Professor

CODE Magazine

Authored articles with content focusing on Power BI, Tableau, data visualization best practices, and Excel Power Query

Contributing Author

UMBC Training Centers

Teach courses to government agencies on Python, R, Excel, and machine learning

Data Science Instructor

Cornell University

Facilitating courses for predictive analytics, R, Python, and Excel optimization models for data science certifications, including engaging with students, grading projects, and designing additional projects to improve student experiences

eCornell Course Facilitator

Accelare

Created Power BI dashboards utilizing design principles on the front end, and DAX languages and multiple data sources on the back end to build out data visualizations to be leveraged by different business departments and levels of users. Provided Accelare consulting staff with training on methods and approaches to leveraging Excel’s functionality to provide more effective and efficient client solutions. Project manager for predictive analytics Medicaid project. Designed and developed Microsoft Power BI metrics designed to be incorporated with Accelare’s WorkFit software that strategy to execution to numerous Fortune 500 companies. Provided the client analytical support through calculation and analysis the modeling of their employment data. Combined this data with allocated cost totals to transform the unstructured view to a useful visualizations, dashboards, and report, assisting the client in identifying significant cost reductions of over $10 million. Real-time logistics analysis with Splunk (SQL structured database) to reduce revenue losses for a large city transportation system by over $3 million a year by improving efficiency for fixing open ticket gates. Analysis and design of HR organizational charts to streamline personnel structure to a lower cost base by cutting around five percent for each department.

Business Architect

Advanced rollout of the OneClaim global implementation in 23 countries, including translation of system information into five languages, for the largest Pegasystems project in company history designed to save AIG $1 billion a year in total operating costs for processing claims. Conceptualized and configured the AIG claims platform, strengthening platform performance to address operational requirements from use cases to the creation and customization of PegaRULES Process Commander (PRPC) requisites. Conferred with stakeholders worldwide about technical and delivery components of implementation projects. Culled requirements for major projects from end users such as the North American Private Client Group and insurance lines in France.

Business Analyst

Part of Actuarial Student program. Calculated and analyzed deferred annuity GAAP and statutory reserve liabilities for financial reports and statements, encompassing an in-depth range of quarterly and annually prepared exhibits. Documented the account value of over $2 billion in deferred annuities as a valuation actuary role. Analyzed financial statements and drafted reports using SAP accounting software, running financial queries and utilizing SAP reports to deepen analysis of the actuarial projections for the deferred annuity block of business. Evaluated and forecasted the deferred annuity cost (DAC) model as part of an annual review designed to align the projected mortality rates, interest rate credited, interest earned, and the expenses in-line with the observed financial experience of the model over the previous year’s performance. Yearly DAC unlocking process reflected in the reported GAAP revenue statements, and these numbers include an increase of $200 million in reported earnings for the entire deferred annuity block of business in 2013. Modeled annuity product interest rates in accordance with market projected interest rates and guaranteed rates. Produced and validated life insurance and annuity illustrations on multiple software programs leveraged by agents to illustrate life insurance/annuity products to a diverse customer base including high net worth clients. Verified product information, specifications, and assumptions accuracy, such as interest rates and fund values. Crafted testing strategies to verify project insurance information accuracy, originating programs to confirm the use of the correct values throughout key processes from pricing to final insurance software calculations.

Actuarial Assistant

Follow me to see my latest published content on data science, analytics, and visualization! Aficionado of Power BI, AWS, Tableau, and Excel (including Power Query), and currently diving deep into the world of Python, R, and AI (including machine learning).  Designer and developer of business intelligence dashboards and visualizations supporting many business functions and industries.

The latest Power BI updates for November are out! Christopher Wagner, MBA, MVP and I added these newest features to our consolidated updates cheat sheet, along with over four years of previous updates!

As of this month, the new card visual is now generally available, as are the Spark and Impala data connectors. There are also styling updates to the image visuals and functionality updates to the decomposition tree that allow us to expand into more details across all the visual's levels.

On the modeling side, we can now tap into Power BI Modeling with MCP Servers (currently in preview mode). We can also view the semantic model version history and use the TMDL Visual Studio Code extension as they're now both generally available within Power BI.

Check out this overview and please share your favorite parts of this month's updates! #PowerBI #MonthlyUpdates #AlwaysBeLearning

Helen Wall

LinkedIn [in]structor | Data Science Consulting

Power BI Updates - November 2025

A recently introduced (and still in preview mode) feature in Power BI lets us build advanced time intelligence models using either Gregorian or custom calendars (like lunar or retail schedules). 

It takes a bit more work to build these calculations behind the scenes because we need to build out the individual date dimensions (like the week, week of year, and so on) within the calendar table in Power Query (or in DAX). We then need to map these date fields to their date dimensions in the calendar configuration options. We can also map more than one calendar within a single Power BI semantic model!

Finally, when we build DAX time intelligence calculations (like measures), we reference the entire configured calendar table instead of the date field like we do in earlier time intelligence DAX formulas.

If you're wondering how to create a lunar or retail calendar, I'll share more about those topics soon, stay tuned for what's to come! #PowerBI #DAX #TimeIntelligence

Infographic showing how to use advanced time intelligence in Power BI with DAX time intelligence functions (currently in preview mode). 

The workflow has three steps: 
1) Create a calendar to use in Power Query, choosing from Gregorian, Lunar, or Retail calendar types, represented by a database icon with calendar. 

2) Map date fields to date dimensions in the new calendar table, listing fields like Year, Quarter, Quarter of Year, Month, Month of Year, Month of Quarter, Week, Week of Year, Week of Quarter, Week of Month, Date, Day of Year, Day of Quarter, Day of Month, and Day of Week. 

3) Reference this new calendar table within time intelligence DAX functions, showing two columns of function names: Left column includes DATEADD, DATESBETWEEN, DATESINPERIOD, ENDOFWEEK, ENDOFMONTH, ENDOFQUARTER, ENDOFYEAR, STARTOFWEEK, STARTOFMONTH, STARTOFQUARTER, STARTOFYEAR, NEXTDAY, NEXTWEEK, NEXTMONTH, NEXTQUARTER, NEXTYEAR, PREVIOUSDAY, PREVIOUSWEEK, PREVIOUSMONTH, PREVIOUSQUARTER, PREVIOUSYEAR

The new calendar intelligence options in Power BI let us use standard Gregorian calendars as well as custom calendars like lunar patterns to do DAX calculations with.

Here's an example of what a potential lunar calendar looks like. More to come on this topic in the near future, stay tuned! #PowerBI #DAX #TimeIntelligence

Two-month calendar for November and December 2025 showing moon phases including waning crescent, last quarter, first quarter, and full moon on specific dates. 

Useful for lunar tracking and event planning.

The recent introduction of weekly functions to the DAX time intelligence library introduced DAX functions like OPENINGBALANCEWEEK, CLOSINGBALANCEWEEK, STARTOFWEEK, ENDOFWEEK, DATESWTD, TOTALWTD, NEXTWEEK, and PREVIOUSWEEK to our potential calculation options.

Rather than thinking of them as entirely new functions, I find it helpful to think of them as a new group of weekly functions that extends the existing capabilities of the entire DAX time intelligence function family.

Here's how these weekly functions compare to the rest of the existing time intelligence functions! #PowerBI #DAX #TimeIntelligence

Infographic showing DAX time intelligence functions organized by time intervals. 

A ruler graphic illustrates how these functions work like filter calculations. 

Functions are categorized into six columns: 

Day (NEXTDAY, PREVIOUSDAY), 

Week (OPENINGBALANCEWEEK, CLOSINGBALANCEWEEK, STARTOFWEEK, ENDOFWEEK, DATESWTD, TOTALWTD, NEXTWEEK, PREVIOUSWEEK), 

Month (OPENINGBALANCEMONTH, CLOSINGBALANCEMONTH, STARTOFMONTH, ENDOFMONTH, DATESMTD, TOTALMTD, NEXTMONTH, PREVIOUSMONTH), 

Quarter (OPENINGBALANCEQUARTER, CLOSINGBALANCEQUARTER, STARTOFQUARTER, ENDOFQUARTER, DATESQTD, TOTALQTD, NEXTQUARTER, PREVIOUSQUARTER), 

Year (OPENINGBALANCEYEAR, CLOSINGBALANCEYEAR, STARTOFYEAR, ENDOFYEAR, DATESYTD, TOTALYTD, NEXTYEAR, PREVIOUSYEAR), 

and Any (DATEADD, DATESBETWEEN, DATESINPERIOD, FIRSTDATE, LASTDATE, PARALLELPERIOD, SAMEPERIODLASTYEAR). 

Created by Helen Wall.

In the corrplot library in R, we have the option of displaying just the top of a correlation matrix. If we want to do something similar in Power BI, here’s how to do it!

https://lnkd.in/gyfqzqgc

Thanksgiving is both a November holiday and one that involves pie (and often multiple pies). 

Since the US government fixed the date of Thanksgiving as the fourth Thursday of November in 1941, it can potentially occur anytime between November 22nd and November 28th, depending on what day of the week that November began on that year.

As yet another pi (π) day within the Gregorian calendar, this holiday is also worth baking a pie for. As a decimal value, November 27th (11.27) is 3.587π. Thanksgiving can fall anytime between 3.57π (11.22) and 3.59π (11.28), depending on the calendar year at hand.

This year, I made Miso-and-Maple-Pecan Butter Mochi Cake/Pie, courtesy of Bon Appetit recipe library! Happy Thanksgiving to everyone celebrating! #Pi #Pie #Thanksgiving

Happy Thanksgiving image featuring a homemade pecan pie on a white plate with blue trim. 

The pie is mostly intact with two slices cut and removed, showing a dense, custardy filling topped with pecans. 

One slice is visible on a separate plate in the background. Below the image, text reads "Happy Thanksgiving!" followed by a mathematical representation of the possible holiday date range: "November 22, 11.22, 3.57π is less than or equal to Possible holiday date range is less than or equal to November 28, 11.28, 3.59π" - illustrating that Thanksgiving falls between these dates, represented both numerically and as multiples of pi.

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