1z0-1177-26 Questions and Answers

A and B are the intended answers. Oracle Analytics supports constrained or cascading prompts , where a value selected in one prompt restricts the values presented by another. A classic example is selecting a Region first and having a subsequent City prompt display only cities within that region. This improves usability and prevents invalid combinations of prompt values.

Oracle also allows prompt default selections to be derived from server-side variables. These include session variables , which can contain user-specific information initialized when a user signs in, and semantic-model/repository variables, which provide centrally maintained values. Such variables can therefore initialize prompts dynamically rather than requiring hard-coded default selections.

Statements C and D impose restrictions that Oracle Analytics does not require. F directly contradicts Oracle variable support.

There is an important technical issue with this question: Oracle Analytics also supports different prompt forms, including column and variable prompts, so E can be interpreted as generally valid . Consequently, E is a weak distractor and makes the item somewhat ambiguous when interpreted literally. For the supplied two-answer examination key and the specific concepts being tested—constrained prompts and variable-based defaults— A and B are the intended selections .

Reference Topic: Formatting Data and Managing Filters, Selection Steps, and Variables — Dashboard Prompts and Variables

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The scheduled job instance is skipped . Oracle Analytics Publisher defines a Schedule Trigger as a SQL query that is executed when the scheduled report job is triggered, before the report itself runs. The returned result determines whether the execution condition has been satisfied.

Oracle states explicitly that if the trigger SQL returns data , the associated report job executes. If the SQL query returns no data , the job instance is skipped. This mechanism allows report execution to depend on a business or technical condition. For example, a report could execute only after an ETL process has completed, only when transactions exceed a specified amount, or only when new records have appeared.

The trigger doesn't convert the job into a bursting job, nor does Publisher execute an empty report merely with a warning. The scheduled job definition also isn't deleted; only that execution instance is skipped. For recurring schedules, subsequent trigger evaluations can still occur according to the configured recurrence and retry behavior.

Therefore, a no-row result from the Schedule Trigger means its condition evaluated as not satisfied and the current job instance is skipped .

Reference Topic: Managing Report Scheduling, Data Sources, Administration, and Translations — Schedule Triggers

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The recommended Oracle Analytics security model is to manage permissions through Application Roles . An application role represents a set of permissions determining what its members can see and do in Oracle Analytics Cloud. Administrators can assign users, groups, and even other application roles as members, allowing authorization to be administered centrally.

This is considerably more scalable than granting permissions individually. For example, an administrator can create or use an application role for Finance Analysts, assign the required analytics privileges and content permissions to that role, and then add all qualifying users to it. When staffing changes occur, administrators modify membership rather than repeatedly redesigning permissions.

Oracle's current guidance explicitly states that it is a best practice to assign permissions through application roles. Predefined roles such as BI Content Author and BI Consumer provide standard capabilities, while user-defined application roles can be created for organization-specific requirements.

Separate catalogs and duplicate dashboards would create unnecessary management overhead. Database accounts don't replace Oracle Analytics application-layer authorization.

Therefore, assigning users to Application Roles is the correct scalable approach.

Reference Topic: Managing Administration, Security, and Performance — Application Roles

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A shared Dashboard Prompt with Presentation Variables centralizes user input and allows multiple dashboard analyses to reference the same runtime selection. Oracle defines a Presentation Variable as a variable populated through a dashboard column prompt or variable prompt. Each time the user changes the prompt selection, the presentation variable is assigned the selected value or values.

Analyses on the dashboard can then reference the variable in filters, expressions, titles, or other supported locations. This allows a department, fiscal period, region, or comparable filter criterion to be selected once and reused across multiple dashboard components.

The architecture substantially improves maintainability because the dashboard-level interaction is managed centrally rather than requiring a separate prompt or manually maintained filter mechanism for every analysis. Independent prompts would recreate the exact maintenance problem stated in the scenario. Conditional Formatting changes visual presentation rather than providing shared filtering, while exporting analyses creates static outputs and eliminates the interactive dashboard experience.

Therefore, the correct design is A. Use a shared Dashboard Prompt with Presentation Variables .

Reference Topic: Designing, Creating, and Enhancing Dashboards — Dashboard Prompts and Presentation Variables

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Oracle Analytics Agents separate the execution condition from the content to be delivered . The Condition tab determines whether the agent should execute. The author can create a new condition or browse to an existing condition based on an analysis. For a condition based on an analysis, Oracle evaluates whether the analysis returns results that satisfy the configured criteria.

The actual payload is configured independently on the Delivery Content tab . Here, the author selects the analysis or dashboard page to deliver and specifies parameters such as subject, output format, and whether results are delivered directly, as an attachment, or as a link where supported.

The Destinations tab determines where content is sent, not whether the condition evaluates to true. The current Oracle documentation identifies the Actions tab as reserved rather than as the location for row-count conditions. The Recipients tab identifies users, application roles, or email recipients but doesn't determine the report output itself. Dashboard prompts are interactive filtering controls, not Agent execution triggers.

Therefore, the required configuration is Condition tab for conditional execution plus Delivery Content tab for the actual analytical content .

Reference Topic: Managing Administration, Security, and Performance — Agents, Conditions, and Delivery Content

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Conditional Formatting is specifically designed to modify the visual representation of data when defined conditions are satisfied while leaving the underlying values unchanged. The analyst can establish rules such as Sales greater than or equal to Target and apply one format, while values below Target receive a different format.

Oracle Analytics supports conditional rules based on measures, attributes, thresholds, percentages, and expressions. Formatting can include font characteristics, cell presentation, images, backgrounds, and visualization-specific properties. Oracle's examples include stoplight-style formatting in which low, medium, and high values receive different visual treatments.

This functionality affects presentation only; it doesn't alter the source Sales values or change the actual calculation. That directly satisfies the requirement.

A Repository Variable stores centrally maintained values and isn't itself a visualization rule. Selection Steps determine which members appear after query aggregation. A Subject Area Filter limits the data returned or made available rather than simply changing its appearance.

Consequently, the appropriate feature for showing above-target values in green and below-target values in red is Conditional Formatting , making A correct.

Reference Topic: Formatting Data and Managing Filters, Selection Steps, and Variables — Conditional Formatting

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The correct settings are User Can Refresh Report Data and User Level caching . Oracle Analytics Publisher defines User Level caching as maintaining a separate cache for each user. With this option enabled, the cached data presented to one user comes from that user's private cache rather than a cache shared with other consumers. This is particularly relevant when report results contain user-sensitive or security-filtered information.

The User Can Refresh Report Data property addresses the second requirement. When enabled, Publisher provides the user with the ability to request a refresh from the Report Viewer. Publisher then generates a new data set instead of continuing to use the existing cached copy.

Caching Duration only controls how long cached data remains valid; setting it to zero does not establish user-specific isolation as described in the scenario. Disabling data caching would eliminate the caching requirement altogether rather than maintaining secure per-user caches. Document Caching stores the generated report document—data plus layout—not merely the parameter list. Clearing all caches following every execution would undermine the performance purpose of caching.

Therefore, A provides freshness on demand , while D supplies user-level cache isolation .

Reference Topic: Managing and Securing Oracle Analytics Publisher — Report Properties and Caching

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Oracle provides a specific Dashboard Builder procedure for displaying a list of briefing books . The briefing books should be stored in a catalog folder. The dashboard author then drags a Folder object from the Dashboard Objects pane into the required dashboard section and opens its properties. In Folder Properties , the author specifies the folder containing the briefing books.

At runtime, the Folder object presents the folder's available briefing books to authorized users. Oracle also allows the author to control whether the folder initially appears expanded.

The Add to Briefing Book option performs the opposite task: it adds dashboard-page or analysis content into a briefing book rather than displaying a collection of existing briefing books. Downloading individual PDF versions likewise doesn't create a dashboard-accessible list. Saved Customizations preserve dashboard state and prompt selections, not catalog-folder contents.

Oracle's documented workflow directly specifies: add a Folder object, open Folder Properties, and identify the folder containing the briefing books. Therefore, option A precisely implements the required dashboard behavior.

Reference Topic: Designing, Creating, and Enhancing Dashboards — Briefing Books and Folder Objects

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A Trellis View is the most appropriate visualization for comparing the same measure across multiple dimensional categories. A trellis displays a series of related visualizations in a grid, allowing users to compare equivalent graphical structures across dimension members.

For example, the designer could use Region or Product Category as an outer-edge dimension and Quarter or another analytical dimension within the repeated visualizations. Because every trellis cell follows a consistent graphical framework, differences in sales performance become easier to identify across categories.

Oracle distinguishes between Simple Trellis and Advanced Trellis use cases. Oracle recommends Simple Trellis for general comparisons and Advanced Trellis when analyzing trends. The documentation also advises controlling dimensional density so that each repeated graph remains readable.

A Narrative View renders textual descriptions generated from query results and isn't optimized for comparative multidimensional visualization. A static table can present all values but provides less immediate visual comparison. A KPI is generally intended to summarize performance against targets rather than display a repeated multidimensional comparison across Region, Product Category, and Quarter.

Therefore, Trellis View best satisfies the scenario.

Reference Topic: Managing and Creating Analyses, Views, and Content — Trellis Views

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Analysis criteria are built in the Criteria tab by selecting columns from folders within the chosen subject area. As columns are added, Oracle places them in the Selected Columns pane. The author can then control their sequence directly by dragging selected columns to the desired position.

Column order is significant because it can affect the initial order in which fields appear in certain result views and determines the organizational sequence of criteria. Reordering does not require changing the semantic model or rebuilding the analysis.

Clear Sort removes sorting specifications, such as ascending or descending sort behavior; it doesn't rearrange the position of selected columns. The Results tab is used to inspect and design visual output after criteria have been established. Catalog permissions control object security and aren't involved in analytical column ordering. Column Properties controls formatting, headings, interaction, data format, conditional formatting, and related characteristics but isn't the standard mechanism for rearranging criteria.

Accordingly, the correct workflow is to select the required columns from the subject area and drag them within Selected Columns to establish the desired order . The uploaded Oracle Analytics question source identifies the same workflow.

Reference Topic: Managing and Creating Analyses, Views, and Content — Criteria Tab and Selected Columns

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Runtime Configuration controls Publisher's system-level processing and document-generation behavior. Oracle's Runtime Configuration framework includes settings for different output types, PDF processing and security, FO processing, memory and performance behavior, template processing, report delivery properties, and associated font mappings.

Oracle's runtime configuration file also illustrates settings such as system-temp-dir, PDF compression, PDF security, and font definitions. In the administrative interface, the Runtime Configuration page provides corresponding system-level properties, with some settings also configurable at individual report level. When report-level and system-level settings differ, Oracle can apply the more specific report-level setting where documented.

A Subject Area is a governed analytical data presentation layer and has nothing to do with Publisher document-processing defaults. Presentation Variables capture runtime prompt values. Selection Steps refine displayed members of an analysis.

The uploaded source's explanation explicitly identifies Runtime Configuration as defining system-wide Publisher processing and output-generation behavior. Its extracted “Correct answer” marker is misplaced relative to the options; Oracle documentation confirms that A. Runtime Configuration is the technically correct answer.

Reference Topic: Managing Report Scheduling, Data Sources, Administration, and Translations — Runtime Configuration

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A Top N selection/filtering operation is the feature designed to retain only the highest-performing members according to a selected measure. In this case, Product Category is the dimension and current-quarter Sales is the measure used to rank the categories. Configuring the analytical selection to retain the top five categories produces exactly the required comparison population.

Oracle Analytics supports both selection-step member refinement and explicit Top/Bottom N filtering capabilities. The current Oracle Analytics documentation includes Top N examples that identify the highest attribute values based on a measure, which is precisely the analytical pattern in this question.

The important concept is that the ranking is based on the measure rather than visual styling. Conditional Formatting could visually distinguish high or low Sales values but wouldn't restrict the result to five product categories. Repository Initialization Blocks initialize semantic-model variables and have no role in ranking members. Dashboard Page Style controls appearance and layout rather than result membership.

Therefore, Selection Step with Top N filtering is the best supplied answer because it limits the displayed product categories according to their current-quarter Sales ranking and retains only the five highest performers.

Reference Topic: Formatting Data and Managing Filters, Selection Steps, and Variables — Top N Analysis

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An RTF Subtemplate is designed specifically to centralize reusable report-layout content. Oracle defines a subtemplate as formatting functionality that can be defined once and then reused either multiple times within one layout or across multiple report-layout templates.

Common subtemplate use cases explicitly include headers, footers, address blocks, reusable formatting, formulas, and conditional layout structures . In this scenario, the corporate header and footer can be defined once in an RTF subtemplate, uploaded to the Publisher Catalog, and referenced from each report template. When the common content must change—for example, because of branding or legal requirements—the organization can update the reusable subtemplate rather than manually editing dozens of separate RTF templates.

Separate SQL Data Models control report data, not shared presentation content. Catalog folders can organize templates but don't eliminate duplicate header/footer definitions. Dashboard Prompts are unrelated to Publisher document-template reuse.

Oracle's documentation identifies common headers and footers as primary examples of subtemplate usage. Therefore, the maintainable solution is RTF Subtemplates , making D correct.

Reference Topic: Building and Formatting Reports Using Layout Editor and Template Builder — RTF Subtemplates

The intended administrative function is Manage Sessions . Oracle documents session monitoring as the mechanism for viewing the total number of active sessions and detailed information about currently signed-in users. Available details include the user identifier, browser information, login time, last-access time, and associated query activity.

In current Oracle Analytics Cloud interfaces, this functionality is surfaced through Console → Sessions and Query Logs , where the Sessions section displays the total number of sessions and user details. Earlier and related Oracle Analytics interfaces expose the same capability as Administration → Manage Sessions . Since that is the terminology supplied by the answer options, C is the correct examination response.

Application Roles manage authorization membership rather than active sessions. Save Content with HTML Markup is a specific security privilege controlling whether HTML-bearing content can be saved. Manage Privileges configures functional privileges but doesn't itself provide the active-user session list. Catalog monitoring similarly doesn't answer the requirement to enumerate currently signed-in users.

Therefore, Manage Sessions is the correct functional capability, with Sessions and Query Logs being the current OAC Console presentation of that functionality.

Reference Topic: Managing Administration, Security, and Performance — Monitoring Users and Sessions

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Query caching is specifically designed to improve response time for repeated analytical queries. Oracle Analytics Cloud stores previously computed query results in a local query cache. When a later request can be satisfied from an existing cache entry, Oracle Analytics can return the precomputed result rather than execute another request against the underlying database.

This scenario is particularly suitable for caching because the underlying data changes only once per day. The administrator can therefore maintain a cache lifecycle aligned with the daily refresh process. After source data changes, relevant cache entries should be purged or refreshed to prevent stale results. Between refreshes, frequently repeated analyses can achieve significant performance improvements while reducing database processing, network traffic, and Oracle Analytics processing overhead.

Disabling caching would increase repeated source-system workload. Adding dashboard prompts doesn't inherently reduce query execution cost. Moving analyses into Personal Folders changes catalog organization and access, not query-processing efficiency.

Oracle explicitly states that query caching can dramatically improve query performance by satisfying subsequent requests without accessing back-end data sources. Therefore, D is correct.

Reference Topic: Managing Administration, Security, and Performance — Query Cache Management

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The technically correct combination is A and E . Oracle Analytics Publisher implements cascading parameters primarily through a Menu parameter backed by a List of Values , together with the Refresh other parameters on change option. Oracle states that Menu parameters support partial-page refresh for cascading parameters. When Refresh other parameters on change is enabled on the controlling parameter, Publisher performs a partial refresh of other parameters whose available values depend on the changed value.

For example, a Department Menu parameter can control an Employee Menu parameter. When Department changes, Publisher reevaluates the dependent employee LOV and presents only employees belonging to the selected department.

Multiple Selection does not create or enable cascading behavior. It merely allows more than one value to be chosen from a parameter's list. Therefore, option D in the uploaded source key should not be treated as the mechanism that establishes the dependency. A Date parameter does not provide the required LOV-based cascading model, while Fixed Data does not dynamically reevaluate dependent values.

Accordingly, this question requires a correction from the supplied key: Refresh other parameters on change + Menu parameter is the Oracle-documented implementation.

Reference Topic: Exploring and Creating Reports and Data Models — Cascading Parameters and Lists of Values

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A reusable enterprise analysis intended for multiple departments should normally be stored in a Shared Folder within the Oracle Analytics Catalog. Shared Folders are designed for analytics content that needs to be consumed collaboratively and governed through centrally managed permissions.

Oracle recommends storing shared analytics objects in Shared Folders and assigning appropriate access rights to users or application roles. Administrators can create a structured shared-folder hierarchy and configure folder-level permissions so that contained objects inherit the required access controls. This is substantially easier to govern than maintaining separate copies of an analysis for individual users or departments.

By contrast, My Folders/personal folders are intended for content belonging to an individual user and aren't the appropriate location for enterprise-wide reusable objects. Browser storage and temporary caches aren't catalog repositories and provide neither durable analytics-content management nor centralized authorization.

A Shared Folder therefore enables the same analysis to be maintained once while granting departments the appropriate read, modify, or other access rights through catalog security.

Accordingly, option A provides the appropriate combination of reuse, centralized management, and security .

Reference Topic: Managing and Creating Analyses, Views, and Content — Shared Catalog Folders

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The author should save the filter as a named filter in the catalog . Oracle Analytics distinguishes between inline filters and named filters. An inline filter belongs to one specific analysis, whereas a named filter is stored independently in the Oracle Analytics Catalog and can subsequently be referenced by multiple compatible analyses.

This is particularly useful for centrally reused business criteria. For example, an organization might create a named filter representing a specific State, Quarter, business unit, or product group. Report authors can then apply that saved filter to multiple analyses rather than recreate the filter definition repeatedly. Oracle also notes that when a named filter is edited and saved, changes can propagate wherever the named filter is referenced, improving consistency and maintainability.

Changing AND/OR grouping merely modifies logical relationships between existing filters and doesn't make the filter independently reusable. Drilling changes the current analytical detail level. A dashboard prompt provides runtime filtering but isn't required simply to reuse the same predetermined filter definition.

Therefore, the appropriate reusable object is a Named Filter saved in the Catalog .

Reference Topic: Formatting Data and Managing Filters, Selection Steps, and Variables — Named Filters

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Action Links provide context-sensitive navigation and action execution within Oracle Analytics. They can navigate to BI content, open external web resources, or invoke other supported actions. Presentation variables can participate in navigation scenarios so that contextual values captured at runtime can be supplied when moving between analytical content.

Oracle also explicitly supports conditional Action Links . When an action link is associated with an analysis column, its availability can be controlled by one or more conditions. For example, an escalation action could appear only when Revenue falls below a specified threshold. Oracle documentation describes this as conditionally enabling or displaying the action link according to data-driven criteria.

The remaining statements impose restrictions that do not exist. Action destinations are not limited merely because analyses reside in different catalog folders. Action Links are not restricted to analyses based on one subject area and certainly are not limited to dashboard prompts. Oracle explicitly supports navigation actions that open web pages and other external resources.

Consequently, B and C describe supported Action Link capabilities: runtime contextual navigation and conditional availability.

Reference Topic: Designing, Creating, and Enhancing Dashboards — Action Framework and Conditional Action Links

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Subject Areas provide the business-oriented interface that enables analysts to create governed analyses without writing SQL. Oracle defines subject areas as logical collections of related business information exposed from a deployed semantic model. They contain presentation tables, columns, measures, hierarchies, and other analytical objects that business users can select through the Analysis Editor.

The semantic model hides the complexity of underlying database structures. A user can therefore select concepts such as Customer, Product, Revenue, Quarter, or Region rather than determine physical table names, joins, aggregation rules, or SQL syntax. When an analysis executes, the Oracle Analytics query engine uses the semantic-model metadata to generate the appropriate physical queries against the source systems.

This model combines usability with governance because calculations, relationships, security rules, and business definitions remain centrally managed.

Direct SQL requires technical query knowledge and bypasses much of the business-friendly abstraction the scenario demands. Database triggers serve transactional database functions, while OCI Object Storage is a storage service rather than a semantic reporting interface.

Therefore, Subject Areas are the correct capability for governed, SQL-free business analysis.

Reference Topic: Managing and Creating Analyses, Views, and Content — Subject Areas

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Oracle Analytics supports cross-subject-area analyses , so the appropriate approach is to create the analysis using the primary subject area and then add another compatible or related subject area through the Analysis Editor.

Oracle's documented workflow starts by selecting one subject area and adding the initial analysis columns. The author then uses Add/Remove Subject Areas in the Subject Areas pane to include another subject area and select the additional required columns. Where local dimensions are involved, Oracle recommends including an appropriate measure from each participating subject area so that the semantic model can resolve the query correctly.

The Analysis Editor is therefore capable of querying multiple subject areas when the semantic relationships support the requested combination. Modifying the semantic model simply to expose every required column in one subject area is unnecessary when compatible subject areas already exist. UNION is a set operation used for combining compatible result sets and is not the standard mechanism for selecting related columns across subject areas. MERGE and dashboard prompts likewise do not establish semantic relationships.

Thus, the supported workflow is to create one analysis and add the second related subject area.

Reference Topic: Managing and Creating Analyses, Views, and Content — Cross-Subject-Area Analyses

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XLIFF translation files are Oracle Analytics Publisher's standard mechanism for translating textual content in report templates. XLIFF—XML Localization Interchange File Format—contains translatable strings such as report titles, table headers, labels, and other boilerplate text that appears in generated output.

Publisher can extract those strings from an RTF template, allow them to be translated into one or more languages, and then associate each translated XLIFF file with the original template under the corresponding locale. At runtime, Publisher evaluates the user's selected Report Locale and automatically selects the matching localized template or XLIFF translation according to its locale fallback rules.

This supports a single underlying report definition while presenting labels in French, Japanese, English, or other configured languages.

Report Bursting controls splitting and delivery rather than language translation. Repository Variables store shared semantic values, while Dashboard Prompts collect user selections and don't provide template-localization infrastructure.

Therefore, XLIFF translation files directly satisfy the requirement for automatically localized report labels based on the user's selected language or report locale.

Reference Topic: Managing Report Scheduling, Data Sources, Administration, and Translations — XLIFF Localization

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A Session Variable is the appropriate choice because its value is associated with an individual user's Oracle Analytics session. Oracle states that session variables are initialized when a user signs in and remain available throughout that user's browsing session. A non-system session variable can therefore hold contextual values such as the user's department, organizational unit, or SalesRegion .

For this scenario, an initialization block can retrieve the user's assigned region during authentication. An analysis can reference that session variable in a data filter, causing each user to receive automatically filtered results without entering a region manually. Oracle explicitly uses user department and sales region as examples of session-variable values.

A Presentation Variable is normally populated interactively through a dashboard or analysis prompt, which violates the requirement for no manual input. A semantic model/repository variable generally holds a value shared more broadly rather than a user-specific login value. A Request Variable temporarily overrides a session variable for an individual request.

Therefore, Session Variable directly provides the required user-specific, login-initialized analytical context.

Reference Topic: Formatting Data and Managing Filters, Selection Steps, and Variables — Session Variables

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Action Links enable context-sensitive navigation from analytical content to related analyses, dashboards, web pages, or other supported targets. An action link can be associated with a column heading, column value, or hierarchy-level value in an analysis. When invoked, the link can pass mapped parameters or contextual information to the destination.

This makes Action Links appropriate for moving from a summarized analytical view into transaction-level detail. For example, a user could select a customer, product, opportunity, or regional value in a summary analysis and open a detailed destination that reflects the selected context. Oracle's Action Framework supports parameter mapping when configuring the target action.

Modern Oracle Analytics workbook Data Actions provide a comparable capability: Analytics Links can pass source-canvas context into another canvas or workbook. The classic Action Link remains the feature explicitly represented in this question.

Repository Variables contain centrally managed values but aren't navigation mechanisms. Runtime Configuration controls Publisher processing settings, and Bursting generates and distributes personalized Publisher documents.

Therefore, B. Action Links is the correct mechanism for contextual navigation from summary to detailed analytical information.

Reference Topic: Designing, Creating, and Enhancing Dashboards — Action Links and Contextual Navigation

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The required capabilities are both available through Column Properties → Column Format . Custom Headings allows the report author to override the default folder or column heading presented in the analysis. This affects the displayed label without modifying the underlying semantic-model column definition. Oracle also permits variables and formatting to be incorporated into custom heading values where appropriate.

Value Suppression controls how consecutive duplicate values are displayed. When the same attribute value occurs repeatedly in adjacent result rows, suppression can display the value only once instead of repeating it on every row. This improves readability in analyses containing grouped or naturally repetitive dimensional data.

Content Paging concerns result retrieval and rendering rather than headings or duplicates. Fixed Headers keeps headings visible during scrolling but does not rename them. Save as Default has a different purpose and does not directly meet either stated requirement.

Oracle's documentation explicitly associates Custom Headings and Value Suppression with the Column Format tab, directly validating B and C.

Reference Topic: Managing and Creating Analyses, Views, and Content — Column Properties and Column Formatting

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