Link

Activate the Oracle Cloud after signing the contract (Order Document):

The Steps to initially activate the Oracle Cloud after purchasing are describes below:

https://docs.oracle.com/en/cloud/get-started/subscriptions-cloud/csgsg/activate-your-order-your-welcome-email.html

With the activation the customer chooses the Account Name (or actually Tenant Name) of their Service, that will be displayed in all subsequent URLs and in the background the Oracle Cloud is physically provided within the chosen Data Center region e.g. EMEA and the Cloud Console will be made available (via DNS configuration in the Oracle Cloud) with the specified Account Name and services like IDCS (Identity Domain Service) are started to maintain the User(s). The Person who conducts this initial activation is also the Cloud Service Administrator and from now on the only person to be able to add further Users as Cloud Service Administrators.

After completion of the steps from the activation link, the user receives another e-mail to his e-mail address with a provisioned user (from IDCS) and a new temporary password to change on the next login.

Provision individual Oracle Cloud Services, such as ADW

The steps to provision Services are described below:

https://www.oracle.com/webfolder/technetwork/tutorials/obe/cloud/adwc/OBE_Provisioning_Autonomous_Data_Warehouse_Cloud_bak/provisioning_autonomous_data_warehouse_cloud.html

Actions after signing in:

https://docs.cloud.oracle.com/iaas/Content/GSG/Tasks/signingin.htm

Advertisements

choosing the right shape for OAC

when provisioning Oracle Analytics Cloud, different shapes are available to run the Service. For shapes based on only 1 OCPU auto scaling will not be available after the initial provisioning of the service. Thus, if the OAC service needs to support scaling after the initial creation a shape with at least 2 OCPUs should be selected:

image

Modelling the calculation of Install base for contracts/subscriptions

For subscription based business, it is important to correlate the new activation’s and ending contracts (churn) with the install base (for a given period). Typically, a customer will have one contract with a certain tariff, provider or product to describe the offered service for the subscription with an activation(start) date and a end date.

Below is an example of how a contract could look like:

image

From an analysis perspective, the result should present a diagram that provides information about the # of activation’s, # of churn (ending contracts) in relation to the # of install base contracts, like below:

image

Baseline for this scenario

For this scenario, a dimensional model with fact and dimensions will be used to describe the data. The contract entity is the fact, while the following other entities are the dimensions used to describe elements of the fact. E.g. the provider dimension contains more detailed information about the provider and the Unit Type and Unit Status dimension contain more detailed information about the device (unit) used for the subscription.

image

Modelling the calculation for # of Activation’s and # of Churn

Keeping in mind the entity for contracts, shown at the beginning, the measures # of activation’s and # of churn can (easily) be calculated by using a count function for the respective date attribute (on the fact) and the join with the time dimension will make sure that the calculation is done correctly for the time element (day level) and higher hierarchy levels (e.g. month/quarter/year).

On the physical model, the date attributes (start date/ end date) of the contract fact are joined with the calendar day of the time dimension:

image

within in the business model, the measures for # of activation and # of churn are added to the subscription fact based on the respective dates using the count function:

image

Once an users drags above elements into a analysis, e.g. at day level

image

the Oracle Analytics Cloud (OAC) will generate the query based on the metadata model (.rpd) like below:

image

This will also work in terms of aggregation levels e.g. for month level

image

Modelling the calculation for # of install base

While the calculation of the above metrics (activation and churn) is straightforward, the calculation for respective install base for a given period is not. This is because the query context for the calculation of the install base cannot be considered. The activation (and end date) can be linked to the time dimension (timeline) for the correct calculation of activation’s and churn. But, this will not work for calculating the install base as the context of the start and end period (of the query) cannot be linked to the timeline.

image

The above diagram shows that the activation and churn can be linked to the time context (timeline) by the respective date itself. But, this context is not available for calculating the valid contracts as install base for a period. To calculate the correct install base, the start date and end date of the contract would need to be linked to the requested query context e.g. install base as of 19.8.2019 (day level) or as of August 2019 (month level).

The only context that would be available would be the current date of the query using the current date (sysdate) to calculate the install base as of today (now). But, this would only provide a current AS-IS view, but not any historical data for a AS-WAS view:

CASE 
WHEN  contract start date <= current date AND 
contract expire date >= current date 
THEN 1 
ELSE 0 
END

The solution to is pre-calculate the install base on day level (for all dimensions, not only the time dimension), within another fact table for the install base.

image

This table could look like the following:

image

and some sample values:

image

This table with can be modeled as an additional logical table source within the BMM Layer of Oracle Analytics Cloud to provide the value of the install base for the given period and dimensions:

image

with the following column source definition for the metric:

image

and the following level definitions:

image

On the physical layer the table needs to be joined with the dimension, like:

image

when running an analysis within BI Answers for activation’s and install base:

image

Oracle Analytics Cloud will execute two queries (for each LTS) to create the combined result:

image

Once another (third) dimension is added to the query, the OAC will use the defined join e.g. inner join to produce the below result:

image

because of the join definition, within the BMM:

image

The resulting database query will also be more complex, as below:

image

Drill-down to contracts from metric

This approach will also allow to use support a drill-down from the metric to a detailed list report. Since, the number of activation’s is calculated on the detailed table, the drill-down from the metric will work easily to the detailed list. The detailed Report needs to be filtered by the higher level elements, which are passed down when a user drills to detail:

image

This drill down method will also work for the install base, which is effectively sourced from another table (LTS).

image

Of course, for this to work correctly, the pre-calculated values for the install base within the aggregation table needs to match with the list of detailed contracts to give the exact results for this context when drilling down.

Conclusion

It is not possible to create a formula within the metadata (.rpd) for calculating the install base. To provide the install base for analysis, the install base needs to be pre-calculated within a dedicated (aggregation) table e.g. during the ETL process. This table can be added to the subject area or business model as an additional LTS. This solution will also support drill-downs by passing the context of the metric as parameters to the detailed report to provide a detailed list of contracts.

Downloads

the .rpd can be downloaded here . The password is ‘Admin123’.

Create Oracle Database user with required privileges

Create Oracle Database user with required privileges

Use the following Oracle SQL to create a database user with the typical privileges to connect and work with the database:

CREATE USER dbusername IDENTIFIED BY dbuserpassword;
GRANT CONNECT TO dbusername;
GRANT CONNECT, RESOURCE TO dbusername;
GRANT UNLIMITED TABLESPACE TO dbusername;

Link

Oracle published results of Customer Support satisfaction survey

Oracle has just published the results of its support satisfaction survey:

https://oradocs-corp.sites.us2.oraclecloud.com/authsite/home/news/article/MySites-Home-News/CORE66BA77F48089483498F3DE2EEF3F8A77/?msgid=home-itk-customer-satisfaction-survey-july2019

And the results are better then expected with a score of 9.11 of 10 (target was 9.01) and an increase from 8.81 of the previous year.

ADWC Performance Benchmark on SSB Schema

The SSB Schema is a generated database schema, that can be used to evaluate the Performance of a Datawarehouse system. This is used to evaluate the performance between ADWC in the cloud and a local Oracle Database which is running within a Virtual Box image on a Laptop. This test is not conducted under test lab conditions and should only provide a rough order of magnitude.

System (Hardware) Baseline

The following instances have been used for the Performance test.

ADWC Trial

based on Hardware specification shown:

image

This instances is only used as reference, since the sizing (with 2 CPUs) and query performance for some queries based on the same SSB schema are publically available.

ADWC

instance which only uses 1 CPU

VM Image

with 4GB Ram

image

and 1 CPU

image

Based on Laptop Host system (Lenovo Yoga 370 Laptop) with:

image

The image runs Oracle Database 12c R2 Enterprise Edition, with no specific/tuned configuration (parameters) for Datawarehousing.

System Schema Baseline

image

Benchmark Performance

For Prologue Queries based on these examples. As mentioned before, for the ADW instance “ADWC Trail”, some queries run times are publically available. These queries have also been executed within the other instances. The runtimes of the ADWC Trail have only been used as reference:

image

SSB Queries, as outlined here and here (Oracle Documentation).  The below shows the query run-times for the ADWC and local Oracle Database (running as a Virtual Box image). The connection to the ADWC instance is made with the high connection type. When using the medium or low connection type, all queries were showing longer response times (as expected). Thus, the high connection type has been used for conducting the Benchmark.

image

The Excel file containing the system baseline in terms of number of records, queries and run-time results can be downloaded here.

Below is a galary of the executed SSB Queries on ADW and Virtual Box Oracle Database 12c:

retrieve Table Sizes in Oracle Database

To retrieve the Table Size of a Database Table in Oracle Database, the following SQL code can be used (also without DBA rights to DBA_Segments Data Dictionary Table):

image

select bytes/1024/1024 MB 
from user_segments 
where segment_name='<Table Name>';

E.g.

select bytes/1024/1024 MB 
from user_segments 
where segment_name='CUSTOMER';

Use of Date data type in Oracle DV

DV allows to make use of individual elements of any Date or Datetime column. Thus, there is no need to calculate the Year portion of a Date as an additional column. For this to work correclty the data type must also be of Date or Datetime on the Database. When importing a text (csv) file to a Oracle Database, a Date may be defined as a text (varchar) field by default. In order to make use of this DV Feature, the data type should be changed to Date data type when importing e.g. with SQL Developer. Otherwise, the field containing the Date may just be displayed with a blue “A” like any other attribute, but not with the purple “clock” to identify a true Date field.

image