Introduction to Oracle Analytics Cloud

The following article provides an outline for Oracle Analytics Cloud. Prophet Analytics Cloud gives the business most extensive cloud investigation in a single unified platform, including everything from self-administration representation and incredible inline information planning to big business detailing, progressed examination, and self-learning examination that convey proactive experiences.

Oracle analytics cloud supports more than 50 data sources and it is an open source framework. The Oracle Analytics cloud provides a complete, connected, combined platform that helps us to boost the power of data and analytics to each and every process, interaction and it also takes the decision in every framework or we can say environment that cloud, on user premises, data centre and computer. With the help of Oracle analytics cloud we can access and analyze data any time.

Why do we Need Oracle Analytics Cloud?

Access and Analyze All Data: Suppose we need to access the all data source across the business, so by using Oracle analytics cloud we can access data and analyzing all that data, after analyzing data we will gate impactful data and this data is helpful for business growth.
Improve Productivity: The Oracle analytics have in built capabilities such as self-administration representation, enterprise reporting etc. By using Oracle analytics cloud we improve productivity and it includes many more options to the user in a single application tool that delivers a unified analytics process.
Faster Time to Insights: This cloud included embedded machine learning to increase the data analysis power and creation of reports. By using Oracle analytics cloud we can quickly predict, desired outcome is more impactful.
Accuracy and Trust: It gives more accurate data as well as we can create a view of data, metrics across the business. With Oracle analytics we can achieve consistency in data and accurate reports.

How does Oracle Analytics Cloud Works?

Oracle analytics has different phases as follows:

1. Prepare Data

Under prepared data we need to follow some steps as follows:

a. Transform data: Data preparation and cleansing is an important task before visualizing a data set. For example, the data set contains sensitive data such as customers’ social data and that data we don’t want to expose so we can hide that data or transform all characters of social security, remove columns from the data set.

b. Prepare data with regular expression: When Oracle analyzes the cloud while preparing data, at that time we can use regular expressions to match specific text patterns in the column data and replace them with different text. Oracle analytics cloud supports regular expression syntax.

It use the different notation as follows:

^: This is used to indicate the start of a string.
$: It used to indicate the end of the string.
|: It is used for OR operators.
.: It is used to search for any characters.
*: It is used to search zero.

c. Explore data flows: In this step we need to modify the data as per the requirement that is the data flow.

d. Analyze data: In this step we need to analyze and explore data.

e. Create aggregated data sets: In data flow we can add different nodes as per the requirement, except the train machine learning model, that is we need to output multiple data sets into a single data flow.

f. Implement incremental processing in data flow: Incremental data processing used to add new data sets available from the database into the data flow. When our data flow runs at that time we need to enable incremental processing data option.

g. Reuse data: In data flow we apply transformation of data sets, we add filters, and remove unwanted data for accurate outcome. If we implement such a parameter in data flow then we can reuse that data without editing it directly.

2. Explore Data

This is the second step in data analytics in that we need to explore data by using different parameters such as creating visualization, capture insights, and building stories etc.

3. Administer Oracle Analytics Cloud

This is the third step in which we set up the stack of data.

Advantages and Disadvantages of Oracle Analytics Cloud

Given below are the advantages and disadvantages mentioned:

Advantages:

It is easy to learn and navigate.
It supports real time reporting.
It is easy to import any kind of data.
It is easy to customize.
It provides data visualization and reporting functionality.
GUI is user-friendly.
It provides advanced analytics functionally to the data.

Disadvantages:

Offline access is difficult.
Language translation is complex.
We can’t show reports in any other tool.
Integration with Excel is difficult.
It has a statistics dashboard and it is difficult to understand.
Sometimes the server is not responding on time.
It does support DB reporting.

Example

Given below is the example mentioned:

First we need to cleanse data by using the groups as shown in the screenshot below.

For example suppose we need to transform the email address, usually email id display using lowercase letters but sometimes it displays in upper case, so we need to change upper case to lowercase as shown in below screenshot as follows.

Now create data flow as shown in below screenshot as follows.

Now add data for data flow as shown in below screenshot as follows.

After that we need to create a data set as shown in the below screenshot.

In this way we can perform different operations on data and all screenshots.

Usage of Oracle Analytics Cloud

It is used for high level development of organizations and provides excellent service.
By using Oracle analytics cloud we can add multiple items into the report from the home page.
It is used to develop different kinds of reports such as sales reports, customer reports and enterprise reporting etc.

Conclusion

From this article we have seen the different examples of Oracle analytics cloud. We also see what are the advantages and disadvantages. From this article we saw how and when we use the Oracle analytics cloud.

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