Author Archives: Allen Rodriguez

DAX optimization becomes dangerous when it starts with formula folklore. Replacing one function with another, adding variables everywhere, or avoiding iterators categorically can produce code that looks ‘optimized’ without improving the workload users actually run. For DP-600, enterprise semantic-model performance is explicitly a measured engineering responsibility, and DAX is only one part of that system. […]

Microsoft Fabric makes both Lakehouse and Warehouse first-class analytical data stores in OneLake, and both use Delta-format storage underneath. That shared foundation can make the choice look cosmetic. It is not. Development style, transaction requirements, data shape, governance, team skills, and downstream workloads determine which experience fits better. The decision sits squarely inside the architecture […]

A semantic model is often drawn as a clean layer between data and reports. In production, it becomes a contract: measures define business meaning, relationships define how filters move, storage mode defines how data is reached, security defines who can see what, and downstream reports depend on names and behavior remaining stable. Those responsibilities are […]

Direct Lake changes how Fabric analytics teams think about the boundary between stored data and semantic models. Instead of importing a second copy of Delta data into the semantic model, Direct Lake can load needed columns from OneLake-backed Delta tables as queries require them. For DP-600, that makes storage mode, semantic-model design, and enterprise-scale performance […]

Deployment pipelines are most valuable when they make a release routine. The goal is not to move a Power BI or Fabric item from one workspace to another with the fewest clicks; it is to make change traceable, testable, explainable, and reversible. That lifecycle perspective fits the deployment and governance skills around PL-300, but it […]

A scheduled refresh looks simple from the Power BI service: a semantic model has credentials, a schedule, and a refresh button. When an on-premises source is involved, however, the request crosses identity, cloud configuration, the gateway service, local networking, drivers, and the source system before a single row can be returned. Understanding that dependency chain […]

Power BI report design is often discussed as a matter of chart choice and color. In production, the harder problem is information architecture: deciding what a page is for, what decision it supports, how much evidence a reader needs, and how the report behaves when data is incomplete, slow, or viewed on a different device. […]

Semantic-model tuning is easy to turn into folklore: remove columns, rewrite measures, add aggregations, change storage mode, reduce visuals, and hope the report becomes faster. A stronger approach starts with evidence. The relevant question for PL-300 and for production teams is not which tuning technique is popular, but which component is actually responsible for user-visible […]

Incremental refresh is often introduced as a way to avoid reloading an entire Power BI table. That is true, but incomplete. The more useful mental model is that Power BI is managing time-based partitions whose boundaries are driven by policy, parameters, and the current refresh date. The operational challenge is therefore state: deciding which historical […]

Choosing between Import and DirectQuery is not a preference about freshness versus speed. It is an architecture decision about where query work happens, which system carries the load, how much latency users can tolerate, and how much operational dependence the reporting layer should place on the source. Those trade-offs sit directly inside the modeling decisions […]

Row-level security in Power BI is often introduced as a DAX rule attached to a role. The real security boundary is larger. The rule depends on identity, workspace permissions, model relationships, data-access mode, role membership, and the assumption that every filter path reaches the rows that should be protected. A rule can be syntactically correct […]

Time intelligence becomes difficult when the business calendar stops looking like a textbook calendar. Fiscal years can start in different months, weeks can follow a 4-4-5 pattern, retail periods can contain 53 weeks, holidays can move, and operational cutoffs can make “day” mean something other than midnight to midnight. A correct DAX function cannot rescue […]

Calculated columns and measures can both be written in DAX, which makes them look like interchangeable ways to express a calculation. They are not. A calculated column is evaluated for each row during refresh and its result is stored in the model. A measure is evaluated on demand under the current filter context. That difference […]

Power BI relationships do more than connect columns. They define how filters move through the semantic model, which makes them part of every measure and every security rule that depends on propagation. A model can contain valid keys and still behave unpredictably if there are multiple possible filter paths, unnecessary bidirectional relationships, or role-playing dimensions […]

Row context answers a deceptively simple question: which row is the expression looking at right now? Calculated columns naturally evaluate once for each row, and iterator functions such as SUMX create a row context over the table they iterate. Trouble begins when a developer expects that current row to behave like a report filter. It […]