#1 most frequent
United States of America
61.2%248 installations of 405
What is Oracle Analytics?
Oracle Analytics is a solution used to visually explore data to create and share compelling stories. Oracle Analytics Cloud is a cloud native service, and Oracle Analytics Server is the on-premise option.
Categories & Use Cases
Videos
Top Performing Features
Single Sign-On (SSO)
Allows users to use one set of login credentials to access multiple applications
Category average: 8.7
Pattern Recognition and Data Mining
Pattern recognition and data mining mean the ability to recognize hidden patterns in large quantities of data.
Category average: 7.1
Multiple Access Permission Levels (Create, Read, Delete)
Multiple access permission levels means that different levels of users have different rights.
Category average: 8.2
Areas for Improvement
Location Analytics / Geographic Visualization
Location analytics is the visualization of geographical or spatial data.
Category average: 7.8
Themeable User Interface (UI)
A themeable user interface means that a specific visual them can be applied to it
Category average: 7.3
Integration with R or other statistical packages
Integration with the open-source R predictive modeling environment.
Category average: 7.3
Who Buys & Uses Oracle Analytics
#2 most frequent
Canada
5.2%21 installations of 405
#3 most frequent
India
4.4%18 installations of 405
A helping hand
Use Cases and Deployment Scope
We use Oracle Analytics Cloud to extract data of colleagues who are present in the company and those who have left the company. It helps us mainiting the database records from name, official email IDs, employee IDs (if they wish to join us back in the future), personal mobile number, personal email ID, their last position in company when they left, and if we can re-hire or not.
Pros
- Sorting out the data on basis of IDs of employee
- Pull report of ex-colleagues by just a quick 2-3 prompts
- Stores data in a form which is easily readable
- Easy extraction of data anytime and anywhere by approved systeme users
Cons
- Sometimes data is too cluttered and is hard to read, and the only solution is to download.
- Would love to see if data can be downloaded in PowerPoint form.
- Sometimes data sheet are empty when too much of data is to be extracted for selection
Return on Investment
- Easy, fast and quick sorting of data and accuracy is flawless
- Data from years of storing can be accessed so fast
- Downloading of report is superfast with correct data
Usability
Alternatives Considered
Oracle Big Data Cloud Service, 360 Business Tool and MySQL
Other Software Used
Microsoft 365 Business Premium, Slack
Oracle Analytics Review
Use Cases and Deployment Scope
We used Oracle Analytics in the past organization, and its primary main function was assisting us in generating various reports, statistics, and graphical displays of various data as needed to be resent. To my knowledge and understanding, there could be various packages that organizations may opt for and hence, a diversity of tools for reporting and graphical visualization.
Pros
- extracting data from database and generating varios reports as required that capture analytical acumen
- visualised reports
- compiling and transforming data from multiple resources
Cons
- pricing
- probably certain AI tools that were not popular at that time
Return on Investment
- no negative impact; the pricing is the only possible concern where certain discounts may be offered
Usability
Alternatives Considered
Oracle Cloud Infrastructure
Other Software Used
6Connex, Workday Human Capital Management, ELMO Software
Oracle Analytics Server.
Use Cases and Deployment Scope
It's just a good tool or application overall to enable us to build reporting. Moreover, it amplifies analytics through its very good use of visualization. It helps with the end-to-end process of the analytical journey, from start or customization to the high level of visualization to the analytics via visualization.
Pros
- Analytics
- Creation
- Visualization
Cons
- Customization
- Integration to other platform.
- Cost
Return on Investment
- Cost
- Implementation
- Customization
Usability
Alternatives Considered
Microsoft Power BI, Tableau Desktop and AFS-Kasse SQL
Other Software Used
NICE CXone Mpower, Oracle Access Management, Microsoft 365
Why OCA?
Use Cases and Deployment Scope
Oracle Analytics Cloud is a pretty good tool for data analytics, visualization, and reporting. It helps to build predictive models. Data models ensure everyone uses a standard set of curated data and definitions, reducing inconsistencies. Application and role-based security specify who is authorized to access what.
Pros
- It enables us to connect and integrate data from various sources, including databases, data warehouses, cloud applications, and big data platforms.
- Data collaboration – OAC enables users to create reports and visualizations based on source data and share those views with other OAC users.
Cons
- Connectivity issues between Oracle Analytics Cloud (public or private) and any private data source that you connect to through a private access channel.
Return on Investment
- Consolidated data. Cloud analytics makes it easier to gain a unified view, bringing together all your disparate data sources from different business systems in one place.
- Data preparation – OAC can ingest data from multiple sources, profiling and cleansing data as loaded into the cloud service.
Usability
My Real Encounter with Oracle Data Visualization Cloud in a Filled Insight
Use Cases and Deployment Scope
Oracle Data Visualization Cloud enables me to reduce time collecting, preparing, modeling, and visualizing data scattered in all ETL services.
Pros
- Collect data across all external data sources regardless of the size.
- Allows users to reuse data models.
- Reduce overall cost since rebuilding models isn’t needed.
Cons
- Unavailability of mobile application, mainly on-premise solutions.
- Lacks enough documentation for collecting data from on-premise services.
Return on Investment
- Reduction in overall operational costs.
- Reduction in resources usage by reusing BW models.
- Data centric rapid decisions.
