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Oracle Analytics | Introduction Image Description

What is Oracle Analytics?

Oracle Analytics is a data platform for business intelligence (BI) that performs a range of data analytics tasks for enterprise. These include ingestion, modeling, preparation, visualization, and enrichment. Some of the main benefits of Oracle Analytics include:Footnote 1

  • Streamlined operations via automated processes.

  • Real-time data, as the platform updates to reflect changes nearly instantaneously.

  • Scalability, because the platform can handle both small and massive amounts of data.

  • Enhanced collaboration over the Oracle Analytics Cloud, where team members can work on data together from anywhere.

  • Wider data connectivity between tasks and departments, because it integrates with other products, even ones outside the Oracle Cloud.

  • Visualizations that facilitate interaction and clear communication.

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Oracle Analytics tutorial curriculum

An introductory Oracle Analytics course can provide an overview of the platform, reviewing its general capabilities, tools, and layout. You can learn how to work with the graphical user interface (GUI) on Oracle Analytics' desktop and web versions. Courses may also cover how to import and analyze datasets, as well as how to create dashboards, visualizations, and reports to share insights. Advanced learners may focus their study on machine learning and prediction models, which allow you to derive better insights from your data.

With edX, you can explore a variety of educational opportunities related to data analytics, data science, and more. A boot camp can provide flexible, hands-on learning for those who want to upskill quickly, while executive education courses are designed with busy professionals in mind. You can also opt for a more comprehensive curriculum with a bachelor’s degree program or, for more advanced learners, a master’s degree program. Find the right learning path for you, with edX.

Explore jobs that use Oracle Analytics

Knowledge of Oracle Analytics can be helpful for a variety of professional roles including:

  • Data scientist or analyst: These professionals examine complex datasets to create reports, visualizations, predictive models, and more.Footnote 2

  • Business analyst: These professionals conduct research into data from various internal and external sources for insights that can be used to drive informed business decisions.Footnote 3

  • Software developer or engineer: These professionals build custom applications for analytics and data management.Footnote 4 By employing Oracle Analytics, software engineers can harness its robust data visualization and analysis functionalities, empowering them to extract valuable insights, enhance software performance, and foster data-informed decision-making throughout the lifecycle of software development and maintenance.

  • Technical writer: These professionals may create blog posts, scripts, documentation, microcopy, and other pieces of written content to help people use the platform.Footnote 5

  • IT support technician: These professionals use their technical knowledge to help people resolve issues they run into, especially those on the on-premise Oracle Analytics Server that may not be able to get assistance from elsewhere.Footnote 6

For data analytics and software engineering roles, it might be beneficial to complete a coding boot camp to learn different programming languages used for analysis, like SQL, R, and Python. With this knowledge, you can leverage the Oracle reporting and analytics platform.

If you're interested in a role where you're going to work with sensitive content from private data sources, you can consider a cybersecurity boot camp to learn more about data governance and protection.

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Frequently asked questions

Oracle Analytics Cloud is a cloud platform that handles data administration and governance functions for BI. It supports the full data analytics workflow, from preparation through modeling, exploration, sharing, and consumption. Oracle Analytics comes in either a Professional or Enterprise plan. The latter provides more robust features like email distribution and pixel-perfect reports. Features in either plan include standalone mobile apps; self-service analytics and workbooks; direct links to data sources and datasets; data flows to prepare data; natural language features; and machine learning capabilities.Footnote 7

Oracle Analytics Cloud comes with machine learning capabilities on both Professional and Enterprise editions. On the platform, you can work with machine learning and predictive models from the Oracle Cloud Infrastructure (OCI), Oracle Database, or Oracle Autonomous Data Warehouse.Footnote 8 Oracle machine learning functionality for low-level tasks doesn't require coding skills, and simplifies workflows with features like premade algorithms and a GUI. Even if you only work with small datasets, you can still use it to mine data or train models that you use for predictions.Footnote 9

Oracle Analytics is a collection of data software tools for BI. Its main functions are data analysis, governance, and administration.

Oracle Analytics is a data analysis platform. It allows you to connect data from a source like Google BigQuery or a SQL database. You can then prepare the data with transformation, insights, or machine learning, before you move on to the modeling phase. Here, you can create self-service analytics datasets for other departments. For data exploration, the platform allows you to create visualizations or generate deeper insights with machine learning. You can share the data in storyboards and use it in apps, chatbots, and more.Footnote 10

Oracle Business Intelligence Enterprise Edition (OBIEE) is a suite of BI tools like Oracle Analytics, except it's primarily on-premises rather than cloud-based. For this reason, the company touted OBIEE as a way for customers to reduce the overall costs of ownership, and realize a greater return on the investments they made toward in-house infrastructure.Footnote 11 In recent years, however, the company has shifted focus away from OBIEE to a unified Oracle Analytics platform, with Oracle Analytics Server as the current on-premise offering.Footnote 12

Oracle Analytics uses SQL in a variety of processes. You can connect to or import data from sources like PostgreSQL, MySQL, and Microsoft SQL Server.Footnote 13 Then, you can use SQL to analyze, model, and create reports. If you pull data from Oracle Database, you can organize it with analytic views and manage it with SQL. Moreover, you can generate SQL scripts from your workflows to automate processes. Apart from Python and R, you can also use SQL for machine learning within the platform.Footnote 14