Seit einiger Zeit ist das ChatGPT von OpenAI in aller Munde, was es alles nicht schon kann. ChatGPT ist eine Text-Basierte Artificial Intelligence Anwendung und kann auch Code schreiben, welches natĂĽrlich super interessant ist. Doch was weiss ChatGPT ĂĽber unser Essbase? Kann es uns helfen bei unseren Fragen ĂĽber Essbase?
Dieser Beitrag ist in Englisch und enthält die Fragen, Antworten in Textform und als Abbildung.
Abbildung 1: Logo von AI Chatbot ChatGPT
Hier sind meine Tests was ChatGPT alles machen kann mit dem Begriff Essbase.
Mein Ziel ist es MDX Code zum Time Balance Last zu bekommen.
Weil der Chatbot sich in seiner Antwort auf vorherige Fragen und Antworte bezieht, gehe ich Schritt für Schritt vor. Hierdurch möchte ich schneller eine gute Antwort auf meine Fragen bekommen.
What is essbase?
Essbase is a multidimensional database management system (OLAP) that is used for business intelligence and performance management applications. It allows users to analyze large amounts of data quickly and easily by providing a flexible, multi-dimensional framework for data storage and retrieval. Essbase can be integrated with other business intelligence tools and can be used to create reports, dashboards, and other data visualizations. It is developed and owned by Oracle Corporation.
Diese Definition ist sehr gut.
Can I use MDX with Essbase?
Yes, you can use MDX (Multidimensional Expressions) with Essbase. MDX is a query language for OLAP databases that is used to retrieve data from multidimensional data sources such as Essbase. It allows you to create calculations and perform complex analysis on the data stored in Essbase by using a set of functions and operators specific to multidimensional data. MDX is a standardized query language and can be used with other OLAP databases like Microsoft Analysis Services (SSAS), IBM Cognos, and SAP BusinessObjects, which makes it a powerful tool for business intelligence and performance management applications.
Auch diese Antwort ist korrekt.
What means Time Balance Last in Essbase?
In Essbase, „Time Balance Last“ is a member property that is used to specify the last period in a time dimension. This member property is typically used to define a dynamic calculation that references the last period in the time dimension, such as calculating a year-to-date or a running total.
When a calculation is set to reference the Time Balance Last member, Essbase will automatically adjust the calculation to use the last period in the time dimension, regardless of when the calculation is run. For example, if the Time Balance Last member is set to December and the calculation is run in January, the calculation will still reference December as the last period.
In summary, Time Balance Last is a property used in Essbase to reference the last period in a time dimension, it could be used in calculations to perform YTD or Running total analysis.
Diese Antwort ist lang und generell korrekt. In Essbase wird die Eigenschaft auf ein Account Element gesetzt und nicht wie bei anderen OLAP Tools in der Abfrage/Berechnung eingebettet.
What is the MDX query for Time Balance Last?
The MDX (Multidimensional Expressions) query for Time Balance Last will depend on the specific structure of your Essbase database and the name of the dimension and member that you want to reference.
A general example of an MDX query to retrieve the Time Balance Last member value in a time dimension called „Time“ could be:
SELECT [Time].LASTMEMBER ON 0,
[Measures].[YourMeasure] ON 1
FROM [YourDatabase]
This query uses the LASTMEMBER function to select the last member of the „Time“ dimension, and then retrieves the value of the measure „YourMeasure“ for that member.
Please note that the names of the dimensions, members, and measures will vary depending on how your Essbase database is structured and how it was named.
Also, keep in mind that the above query is a basic example, and it might not be the best solution for your specific use case, it could vary based on the complexity of your database.
Diese Antwort ist nicht korrekt. In Essbase MDX haben wir kein LASTMEMBER sondern nur LastSibling und LastChild. Die Funktion ist auch of etwas komplizierter.
Can MDX calculate members?
Yes, MDX (Multidimensional Expressions) can be used to calculate members in an Essbase database. MDX provides a set of functions and operators that can be used to perform calculations on the data stored in an OLAP database.
For example, you can use the + operator to add two members together, or you can use the IIF function to create a calculated member based on a specific condition. Some examples of calculations that can be performed using MDX include:
- YTD (Year-to-date) calculations
- Running total calculations
- Ratio calculations
- Percent of total calculations
MDX can also be used to create custom calculations that can reference other members or dimensions in the database, these calculations are called calculated members, which are created by using the MDX script and can be used in the same way as regular members, they are also stored in the database.
It’s important to note that the MDX calculations are performed in the database, not in the client, which is why it’s so efficient to use this language for multidimensional analysis.
Diese Antwort ist teilweise korrekt. Die Outlineformel ist etwas kompliziert beschrieben und MDX kann auch im Client ausgefĂĽhrt werden, welches nicht langsamer sein muss.
Can you give me a YTD calculation for Time Balance Last in MDX?
Sure, here is an example of an MDX query that can be used to calculate the Year-to-date (YTD) value for a measure called
„YourMeasure“ for the Time Balance Last member of a time dimension called „Time“:
WITH MEMBER [Measures].[YTD_YourMeasure] AS
( [Time].LASTMEMBER, [Measures].[YourMeasure] )
/
( [Time].LASTMEMBER.LEVEL.PARENT, [Measures].[YourMeasure] )
SELECT [Time].LASTMEMBER ON 0,
[Measures].[YTD_YourMeasure] ON 1
FROM [YourDatabase]
This query uses the WITH MEMBER clause to create a new calculated member called „YTD_YourMeasure“. The new member is calculated by dividing the value of „YourMeasure“ for the Time Balance Last member by the value of „YourMeasure“ for the parent of the Time Balance Last member.
In this example, the LASTMEMBER function is used to reference the Time Balance Last member, and the LEVEL and PARENT functions are used to reference the parent of the Time Balance Last member.
Please note that the names of the dimensions, members, and measures will vary depending on how your Essbase database is structured and how it was named.
It’s also important to point out that this is just one way to perform a YTD calculation in MDX, there are multiple ways to achieve this, and the best approach will depend on the specific requirements of your application and the structure of your Essbase database.
Diese Antwort ist nicht richtig. Nun, wir lösen es auch anders in Essbase.
Eine andere Frage – versteht es Dense und Sparse Dimensions?
What is a dense dimension in Essbase?
In Essbase, a dense dimension is a dimension that has a large number of members, typically used to represent a dimension with many levels of detail. Dense dimensions are stored in memory and are optimized for fast retrieval of data. They are typically used for dimensions with a large number of members, such as the time dimension in a financial model.
Diese Antwort falsch. Es ist nicht sehr spezifisch, aber beschreibt eine Sparse Dimension.
In Essbase, what is a sparse dimension?
In Essbase, a sparse dimension is a dimension that has a relatively small number of members, typically used to represent a dimension with a lower level of detail. Sparse dimensions are stored on disk and are optimized for efficient storage of data. They are typically used for dimensions with a relatively small number of members, such as the account dimension in a financial model. Unlike dense dimensions, sparse dimension data is stored in a sparse format which means it only stores non-zero data points and the data points that are not stored are assumed to be zero.
Diese Antwort falsch, ziemlich lang und beschreibt eine Dense Dimension.
what is a data block in Essbase?
In Essbase, a data block is a unit of storage that contains the data for a specific combination of dimension members. Each data block corresponds to a unique combination of dimension members, and contains a single data value for that combination of members. Data blocks are organized in a multidimensional array structure, with each dimension represented by a set of blocks. Essbase uses data blocks to store and retrieve data efficiently, by only loading the data blocks that are needed for a specific query. Data blocks are used in both dense and sparse dimensions.
Diese Antwort teilweise falsch. Die „unique combination of dimension members” bezieht sich auf die Sparse Dimensionen und das es nur „a single data value“ hat stimmt auch nicht.
Eine andere Frage – kann ChatGPT ein einfaches Calc Script schreiben?
How to aggregate a dimension Product and Customer for the Actuals Sales Data ?
To aggregate a dimension Product and Customer for the Actuals Sales Data in Essbase, you can follow these steps:
- Create a new dimension called „Actuals Sales Data“ and add the dimensions „Product“ and „Customer“ as children.
- Create a new outline for the „Actuals Sales Data“ dimension, and set the aggregation rule for the „Product“ and „Customer“ dimensions to „Sum“.
- Load the actual sales data into the „Actuals Sales Data“ dimension, making sure to include the product and customer dimension members in the data load.
- Run a query or report that retrieves the actual sales data, grouped by the „Product“ and „Customer“ dimensions.
- Use the aggregate function like SUM, AVG, COUNT or other calculations you may need for the report.
- The result of the query or report will show the total actual sales for each combination of product and customer.
Note: the above steps is a general approach, and the specific details may vary depending on the version of Essbase and the specific requirements of your analysis.
Diese Antwort teilweise falsch. Auch hier wird mehr die Methode in ROLAP beschrieben, als in unser MOLAP.
Write a script to aggregate a dimension Product and Customer for the Actuals Sales Data
I’m sorry, I’m a text-based AI model, I don’t have capability to write scripts but I can guide you on how to write a script to aggregate a dimension Product and Customer for the Actuals Sales Data in Essbase.
- Connect to the Essbase server using the appropriate API, such as the Essbase Java API, the Essbase .NET API, or the Essbase OLEDB provider.
- Open the outline for the „Actuals Sales Data“ dimension, and set the aggregation rule for the „Product“ and „Customer“ dimensions to „Sum“.
- Load the actual sales data into the „Actuals Sales Data“ dimension, making sure to include the product and customer dimension members in the data load.
- Run a query or report that retrieves the actual sales data, grouped by the „Product“ and „Customer“ dimensions.
- Use the aggregate function like SUM, AVG, COUNT or other calculations you may need for the report.
- The result of the query or report will show the total actual sales for each combination of product and customer.
Here is an example of how this script could look like in Python using the Essbase Python API (pyEssbase)
from pyEssbase import Essbase
ess = Essbase(server,user,password)
ess.connect()
ess.open_outline(„Actuals Sales Data“)
ess.set_aggregation_rule(„Product“, „Sum“)
ess.set_aggregation_rule(„Customer“, „Sum“)
ess.load_data(„Actuals Sales Data“, actual_sales_data, [„Product“,“Customer“])
result = ess.run_report(„Actuals Sales Data“,[„Product“,“Customer“],aggregate_function=“SUM“)
ess.disconnect()
Note: This is an example script and would require adjustments depending on the version of Essbase, the specific requirements of your analysis and the way you have your data organized.
Diese Antwort beschreibt ein Skript in Python, welches aber nicht auf Essbase funktioniert. Es ist sehr auf relationale Datenbanken orientiert.
Fazit
In einem Satz – Beeindruckend was ChatGPT jetzt schon kann, aber es sollte noch etwas mehr unsere Essbase Dokumentation lesen, denn für diesen Bereich ist es noch nicht ausreichend. Es ist schon / noch sehr Microsoft ROLAP orientiert.
Es hat also noch Sinn, um das Blog weiter zu schreiben.
Ihr Philip Hulsebosch
