Customer Segmentation with Data Flow in Oracle Analytics

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Customer Segmentation Analysis is a popular business issue, especially in Retail domain, where companies need to discover the data and group customers based on customer attributes, such demographics and customer transactions. The results of customer segmentation analysis let the retailers understand the customers’ behavior and create effective campaigns.

This tutorial will describe the usage of Data Flow in Oracle Analytics for resolving the Customer Segmentation problem (the data is hosted in Autonomous Data Warehouse).

CodingSight - Customer Segmentation with Data Flow in Oracle Analytics
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Import JSON Data with SQL Developer Web into Autonomous Database

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Twitter Activity provides loads of information for analysis. You can learn your target audience better, determine the most popular content, check the right time when your visitors are more active, etc. By getting the Twitter Activity data and putting it into the advanced analytical systems, you can correlate that data with other essential information from different sources. The prospects are tremendous.

In this article, we’ll explore the case of importing the Twitter data with the help of SQL Developer Web into an Autonomous Database. The imported Twitter dataset is in JSON format. Thus, you’ll need to work on how to import JSON data into Autonomous Database.

CodingSight - Import JSON Data with SQL Developer Web & Autonomous Database
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Financial Dashboard With Oracle Visualization Desktop

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Oracle Analytics Cloud (OAC) is a single cloud-based platform for data preparation, in-depth analytics, and comprehensive detailed reporting with customizable visualization in one solution. Oracle Business Intelligence Analytics helps to improve planning and make better-grounded decisions to achieve objectives faster and with less effort. Users can easily load the data from both internal and external sources into the system and report the results.

CodingSight - Financial Dashboard With Oracle Visualization Desktop
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Setting Up the Data Flow in Oracle Analytics

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The traditional approach to the transformation process (Extract, Load, Transform) requires that technical users get involved directly. They execute connection to data sources, the transformation of data, and provide final datasets to business users. The process often requires much time whenever business users ask for more information or due to changes/updates in business logic. Then, technical users have to revert datasets and transformations.

CodingSight - Build Data Flow with Oracle Analytics
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Advanced Analytics with Oracle Data Analytics – Handling with Express Builder Functionality

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This article completes the series of posts dedicated to Advanced Analytics with Oracle Data Analytics. Previously, we explored such metrics as Reference Line and Forecast Line in Part 1, and Outliers, Clusters, and Explain features in Part 2. The drag-and-drop methodology helps to build your informative and interactive visuals to view the data.

This part of the material will focus on the Express Builder functionality. This feature is especially helpful for advanced users who possess a deeper understanding of data science and statistics. It is necessary because users need more control over advanced functions and parameters. It also offers running Python scripts for data analysis.

CodingSight - Advanced Analytics with Oracle Analytics Part 3
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Learning Advanced Analytics Features with Oracle Analytics: Outliers and Clusters

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This is the second part of the material dedicated to Oracle Analytics. In Part 1, we started our journey and learned to create Reference Line, Forecast Line with Sales data. It let us get some essential remarks about the products with outstanding performance or relations between Sales and Profit.

In this part, we are going to continue using Advanced features. Here, our goal is to create Outliers and Clusters to identify abnormal data points in datasets and identify the grouping of customers.

CodingSight - Advanced Analytics with Oracle Analytics
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Introduction to Advanced Analytics Features in Oracle Analytics

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Advanced Analytics is a mandatory trend for Business Intelligence platforms and Self-service Analytics tools. It offers a set of statistic functions and algorithms, such as trending, forecast, etc. They help business users, analysts, and others specialists to deep dive into data insights for making better business decisions.

The current article is the first part of the series dedicated to the usage of Advanced Analytics with Oracle Analytics and data hosted in Oracle Autonomous Data Warehouse (ADW). It is not going to cover all the details about statistic functions, algorithms, or probability functions. We are going to discover prebuilt Advanced Analytics features developed in Oracle Analytics.

CodingSight - Advanced Analytics with Oracle Analytics Part 1
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Oracle Data Integrator Tutorial: How to Import Multiple Raw Files into Oracle Autonomous Data Warehouse

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When you build an ETL / ELT enterprise system, you need the Data Integration tools, such as Microsoft SQL Server Integration Service, Oracle Data Integrator (ODI), Talend, etc. These tools help you to integrate, transform, and load data from the source to the destination location.

The current article is the Oracle Data Integrator tutorial, that will explain loading multiple datafiles into an Autonomous Data Warehouse (ADW). This tool is an ELT (extract, load, transform) solution with a graphic interface, built by Oracle. It lets the users build, manage, and maintain the data integration process.

CodingSight - Importing Data into an Oracle Autonomous Data Warehouse using Oracle Data Integrator

In our case study, the system receives the Sales data files from a database. The Oracle Data Integrator needs to pick up all data files to load into the Oracle Autonomous Data Warehouse.  

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Sales Analysis with Power BI Desktop and Autonomous Database

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Oracle Autonomous Data Warehouse (ADW) is a fully managed and high-performance solution, turned and optimized for Data Warehouse workload. It means you don’t need to take more effort and resources (DBA role) to manage the database and optimize the workload.

Power BI Desktop is a business analytics service by Microsoft. It offers interactive visualizations and business intelligence capabilities with a simple interface, letting the end-users create reports and dashboards.

The current article describes the process of creating a Sales Analysis with Power BI Desktop and data hosted in Oracle Autonomous Data Warehouse.

CodingSight - Sales Analysis with Power BI Desktop and Autonomous Database
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