Microsoft Excel Data Analysis and Business Modeling [Book]

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Microsoft excel 2016 data analysis and business modeling sample files free

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Microsoft excel 2016 data analysis and business modeling sample files free

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Microsoft excel 2016 data analysis and business modeling sample files free -

Without this feature, admins are first required to detach the database and then attach the new version of the database. This leads to downtime when the database is unavailable to users, and queries against it will fail. When this new flag is specified, version 1 of the database is deleted atomically within the same transaction with no downtime. However, it comes at the cost of having both databases loaded into memory simultaneously. This improvement allows many-to-many relationships between tables where both columns are non-unique.

A relationship can be defined between a dimension and fact table at a granularity higher than the key column of the dimension. This avoids having to normalize dimension tables and can improve the user experience because the resulting model has a smaller number of tables with logically grouped columns. Many-to-many relationships require models be at the and higher compatibility level. These settings are already available for Azure Analysis Services.

There are no discontinued features announced with this release. Building on the success of Tabular mode first introduced in SQL Server Analysis Services , this release makes tabular models more powerful than ever. In the Analysis Services product lifecycle, these modes are mature. There are no new features for either of these modes in this release.

However, bug fixes and performance improvements are included. While it's important to learn about all the new features, it's also important to know what is being deprecated and discontinued in this release and future releases. To take advantage of many of the new features and functionality described here, new or existing tabular models must be set or upgraded to the compatibility level.

Models at the compatibility level cannot be deployed to SQL Server SP1 or earlier, or downgraded to lower compatibility levels. To learn more, see Compatibility level for Analysis Services tabular models. In Visual Studio, you can select the new compatibility level when creating new tabular model projects. It's important to keep in mind, once you upgrade an existing model to , you can't downgrade.

Be sure to keep a backup of your model database. When it comes to importing data from data sources into your tabular models, SSDT introduces the modern Get Data experience for models at the compatibility level. The modern Get Data experience provides immense data transformation and data mashup capabilities by using the Get Data query builder and M expressions. The modern Get Data experience provides support for a wide range of data sources.

Going forward, updates will include support for even more. The modern Get Data experience and M mashup capabilities do not apply to existing tabular models upgraded from the compatibility level to The new experience only applies to new models created at the compatibility level.

This release introduces encoding hints, an advanced feature used to optimize processing data refresh of large in-memory tabular models. Value encoding provides better query performance for columns that are typically only used for aggregations.

Hash encoding is preferred for group-by columns often dimension-table values and foreign keys. String columns are always hash encoded. Numeric columns can use either of these encoding methods. When Analysis Services starts processing a table, if either the table is empty with or without partitions or a full-table processing operation is being performed, samples values are taken for each numeric column to determine whether to apply value or hash encoding.

By default, value encoding is chosen when the sample of distinct values in the column is large enough - otherwise hash encoding usually provides better compression. It is possible for Analysis Services to change the encoding method after the column is partially processed based on further information about the data distribution, and restart the encoding process; however, this increases processing time and is inefficient.

The performance-tuning whitepaper discusses re-encoding in more detail and describes how to detect it using SQL Server Profiler. Since aggregation over hash-encoded columns is slower than over value-encoded columns, value encoding may be specified as a hint for such columns. It is not guaranteed that the preference is applied.

It is a hint as opposed to a setting. To specify an encoding hint, set the EncodingHint property on the column. Possible values are "Default", "Value" and "Hash". In tabular models, you can model parent-child hierarchies. Hierarchies with a differing number of levels are often referred to as ragged hierarchies. By default, ragged hierarchies are displayed with blanks for levels below the lowest child.

Here's an example of a ragged hierarchy in an organizational chart:. This release introduces the Hide Members property. You can set the Hide Members property for a hierarchy to Hide blank members. When set to Hide blank members , and the model deployed, an easier to read version of the hierarchy is shown in reporting clients like Excel. You can now define a custom row set contributing to a measure value.

Detail Rows is similar to the default drillthrough action in multidimensional models. This allows end-users to view information in more detail than the aggregated level. You can right-click a cell with an aggregated value from the measure and then click Show Details to view the detail rows.

By default, the associated data in the Internet Sales table is displayed. This limited behavior is often not meaningful for the user because the table may not have the necessary columns to show useful information such as customer name and order information. The Detail Rows Expression property for measures allows model authors to customize the columns and rows returned to the end-user. The following example defines the columns to be returned for rows in the Internet Sales table in the sample Adventure Works tabular model:.

With the property defined and the model deployed, a custom row set is returned when the user selects Show Details.

It automatically honors the filter context of the cell that was selected. In this example, only the rows for value are displayed:. In addition to measures, tables also have a property to define a detail rows expression. The Default Detail Rows Expression property acts as the default for all measures within the table.

Measures that do not have their own expression defined inherits the expression from the table and show the row set defined for the table. This allows reuse of expressions, and new measures added to the table later automatically inherits the expression.

The following DAX query returns the row set defined by the detail rows expression for the measure or its table. If no expression is defined, the data for the Internet Sales table is returned because it's the table containing the measure.

This release introduces object-level security for tables and columns. In addition to restricting access to table and column data, sensitive table and column names can be secured.

This helps prevent a malicious user from discovering such a table exists. For example, the following code helps secure the Product table in the sample Adventure Works tabular model by setting the MetadataPermission property of the TablePermission class to None. This release includes improvements to Dynamic Management Views DMV for tabular models at the and compatibility levels. Tabular and higher models show dependencies between M partitions, M expressions and structured data sources.

To learn more, see the Analysis Services blog. For example, the Explore feature in Excel Pivot Tables allows the user to cross-drill to dimensions related to the selected measures. This release corrects the cardinality columns, which were previously showing incorrect values. Previously, it was common to specify multi-value filters using the logical OR operator, like in the following measure expression:. In this case, the IN operator refers to a single-column table with 3 rows; one for each of the specified colors.

Note the table constructor syntax uses curly braces. The IN operator can also be used effectively with table constructors. For example, the following measure filters by combinations of product color and category:. By using the new IN operator, the measure expression above is now equivalent to the one below:. The following features are deprecated in this release:.

SQL Server Analysis Services includes many new enhancements providing improved performance, easier solution authoring, automated database management, enhanced relationships with bi-directional cross filtering, parallel partition processing, and much more. At the heart of most enhancements for this release is the new compatibility level for tabular model databases. This new functionality helps lower Total Cost of Ownership TCO by supporting more users on fewer, more powerful enterprise servers.

Performance and scalability testing showed significant gains in query throughput when running SQL Server SP1 Analysis Services on large multi-node enterprise servers.

While most enhancements in this release are specific to tabular models, a number of enhancements have been made to multidimensional models; for example, distinct count ROLAP optimization for data sources like DB2 and Oracle, drill-through multi-selection support with Excel , and Excel query optimizations.

For tabular models, metadata operations in SSDT are much faster than tabular or models. By comparison, on the same hardware, creating a relationship on a model set to the SQL Server compatibility level with 23 tables takes 3 seconds, whereas the same relationship on a model created set to compatibility level takes just under a second.

Other Analysis Services project templates for multidimensional and data mining solutions are also included, but at the same functional level or as in previous releases. Display folders are now available for tabular models. Defined in SQL Server Data Tools and rendered in client applications like Excel or Power BI Desktop, display folders help you organize large numbers of measures into individual folders, adding a visual hierarchy for easier navigation in field lists.

New in this release is a built-in approach for enabling bi-directional cross filters in tabular models, eliminating the need for hand-crafted DAX workarounds for propagating filter context across table relationships.

Filters are only auto-generated when the direction can be established with a high degree of certainty. If there is ambiguity in the form of multiple query paths across table relationships, a filter won't be created automatically. You can now store translated metadata in a tabular model. Metadata in the model includes fields for Culture , translated captions, and translated descriptions.

See Translations in tabular models Analysis Services for details. You can now upgrade an or tabular model to when the model contains pasted tables. When deployed in a database, a calculated table is indistinguishable from regular tables.

There are several uses for calculated tables, including the creation of new tables to expose an existing table in a specific role. The classic example is a Date table that operates in multiple contexts order date, ship date, and so forth. By creating a calculated table for a given role, you can now activate a table relationship to facilitate queries or data interaction using the calculated table.

Another use for calculated tables is to combine parts of existing tables into an entirely new table that exists only in the model. See Create a Calculated Table to learn more. With formula fixup on a tabular model, SSDT will automatically update any measures that is referencing a column or table that was renamed.

To support multiple environments, like Test and Pre-production environments, Visual Studio allows developers to create multiple project configurations using the configuration manager. Multidimensional models already leverage this but tabular models did not. With this release, you can now use configuration manager to deploy to different servers. In this release, an Analysis Services instance in Tabular server mode can run tabular models at any compatibility level , , The latest SQL Server Management Studio is updated to display properties and provide database model administration for tabular models at the compatibility level.

This release includes new parallel processing functionality for tables with two or more partitions, increasing processing performance. There are no configuration settings for this feature. For more information about configuring partitions and processing tables, see Tabular model partitions.

In the Select Users or Groups dialog, set the Locations for the computers domain and then add the Computers object type. For more information, see Grant server admin rights to an Analysis Services instance. Database Consistency Checker DBCC runs internally to detect potential data corruption issues on database load, but can also be run on demand if you suspect problems in your data or model.

DBCC runs different checks depending on whether the model is tabular or multidimensional. You can set up live data streams to monitor server activity in real time, keep session data loaded in memory for faster analysis, or save data streams to a file for offline analysis. This release includes PowerShell enhancements for tabular models at compatibility level Other SSAS PowerShell cmdlets may be updated in a future release to use the new tabular metadata exceptions will be called out in the release notes.

Using the latest version of SSMS , you can now create scripts to automate most administrative tasks for tabular models. The payload is a JSON document that can be as minimal as the example shown above, or highly embellished with the full set of object definitions. Other commands, such as Process, can also be scripted in this release.

Script support for many other actions may be added in a future release. Updates to the formula bar help you write formulas with more ease by differentiating functions, fields and measures using syntax coloring, it provides intelligent function and field suggestions and tells you if parts of your DAX expression are wrong using error squiggles.

This release now includes support for variables in DAX. Variables can now store the result of an expression as a named variable, which can then be passed as an argument to other measure expressions.

Once resultant values have been calculated for a variable expression, those values do not change, even if the variable is referenced in another expression.

For more information, see VAR Function. With this release, DAX introduces over fifty new functions to support faster calculations and enhanced visualizations in Power BI. You can now save incomplete DAX measures directly in a tabular model project and pick it up again when you are ready to continue. Analysis Services Management Objects AMO is updated to include a new tabular namespace for managing a Tabular Mode instance of SQL Server Analysis Services, as well as provide the data definition language for creating or modifying tabular models programmatically.

Visit Microsoft. Tabular to read up on the API. The new assembly separates out common classes like Server, Database, and Role that have broad application in Analysis Services, irrespective of server mode. Previously, these classes were part of the original Microsoft. AnalysisServices assembly. Moving them to a new assembly paves the way for future extensions to AMO, with clear division between generic and context-specific APIs.

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