A good volume of data, paired with insightful analysis, makes for a powerful data-driven marketing strategy. OLAP, or online analytical processing, can help with this. Market research needs to be fast, intuitive, and interactive to help boost decision making. OLAP is the perfect partner for this market research and analysis.
What is OLAP?
Online Analytical Processing (OLAP) is a category of software technology that enables analysts and managers to inspect data from multiple databases simultaneously. The process provides fast, intuitive, and interactive access to multidimensional data. It also helps analysts extract a wide variety of insights.
The goal of OLAP is to pre-calculate and pre-aggregate data to make analysis faster. This pre-aggregated and pre-calculated data is stored in an OLAP database, or OLAP cube.
An OLAP cube is a screenshot of data at a specific point in time. OLAP cubes can store and analyze multidimensional data in a quick but logical manner. Usually, marketers use spreadsheets to perform two-dimensional data analysis. However, OLAP contains multidimensional data, which is why we use OLAP cubes (or hypercubes).
OLAP cubes are not strictly cuboids and can be different dimensions. This is just the name given to the process of linking data from different dimensions.
How Does OLAP Work?
There are multiple steps of OLAP:
- First, data is first extracted from various data sources and formats, like text files and spreadsheets. This data is then stored in the Data Warehouse.
- Next, the data is cleaned, transformed, and stored in OLAP Cubes
- Once in the OLAP cubes, information is then pre-calculated and pre-aggregated in advance for further analysis
- Lastly, the user gets the data from the OLAP cubes by running queries against them
OLAP vs. Traditional Data Mining
Typically, data is distributed throughout multiple data sources and formats. The OLAP process involves extracting data from the various data repositories, making them compatible, and moving them to the data warehouse.
First, OLAP identifies the dimensions, measures, and attributes in this multidimensional data model. It can also determine the relationships within each dimension. Then, the resulting data model will be loaded onto a multidimensional OLAP Cube.
We use four dimensions to organize the data in OLAP cubes:
- Product: “Product” shows how data varies with each product.
- Customer: “Customer” shows how data varies by the customer or geographic area.
- Channel: “Channel” shows how data varies according to each distribution channel.
- Time: “Time” shows how data changes over time.
Next, OLAP identifies levels of summarization within each dimension. Lastly, with data in OLAP cubes, analysts can build reports, visualizations, and dashboards. With these analyses, marketers can take action to increase sales and profit.
Online Analytical Processing #OLAP is the analysis of multidimensional data, using three operators: drill-down, consolidation, and slice and dice. Drill-down analysis allows users to view underlying details. Consolidation aggregates the available data. pic.twitter.com/XubTJUDClK
— zsah (@zsahLTD) March 29, 2020
Examples of OLAP in Marketing
Many industries, including digital marketing, health care, finance, eCommerce, and manufacturing, can use OLAP in their marketing. Here is a case study in the eCommerce sector:
OLAP for eCommerce Businesses
Imagine an eCommerce store. The marketing team hasn’t met its budgeting numbers. Marketing research analysts need to develop a successful marketing strategy.
The goal is to increase company profits by increasing overall sales volume and, more specifically, sales of higher-margin products.
Marketing analysts are looking for answers to questions like:
- What products are valuable?
- What are our monthly, quarterly, and annual sales and profit analyses?
- Are there any regional, seasonal, or industry trends?
- What is the sales analysis of high margin products?
- What is the performance analysis of each distribution channel?
- Who are our customers? What products are they buying?
- How can we analyze and target specific market segments?
- What is the defect analysis for various products?
- What is the raw material purchase and product manufacturing forecast according to the sales target?
In this situation, OLAP in marketing can work wonders. It answers the above questions with pre-calculated data. Then, the data is transformed into various tools, including data visualizations, reports, and dashboards.
Benefits of OLAP in Marketing
There are many benefits of using OLAP in marketing. Here are just a few:
- OLAP gives a multidimensional data representation to organize and analyze data
- OLAP provides pre-calculated data to different data mining tools, business modeling tools, performance analysis tools, and reporting tools
- Pre-aggregate values in OLAP Cubes lend to faster response times
- OLAP provides a single source of data for all end-users, which makes queries easy to run
- The learning curve is minimal
OLAP can help with:
- Financial Modeling
- Sales Analysis
- Market Research Analysis
- Customer Analysis
- Defect Analysis
- Cost Analysis
- And more
Data Warehouse vs Database
Data warehouses and databases are both relational data systems, but were built to serve different purposes. A data warehouse is built to store large quantities of historical data and enable fast, complex queries across all the data, pic.twitter.com/c4aSO42FzY
— rashid (@99Albusafi) April 13, 2020
Top OLAP Marketing Tools
You can use OLAP tools to analyze large volumes of multidimensional data from different perspectives. They make it easy to filter, analyze, and visualize key data insights. These tools are often part of a Business Intelligence Suite.
OLAP marketing tools should have the following features:
- The ability to analyze large volumes of (big) data
- The ability to perform analytical operations
- A high degree of interactivity
- Fast response times
- Different types of data visualizations
- The ability to analyze why things happen
Some OLAP tools used in marketing include:
IBM Cognos is a web-based reporting and analytical tool to help you understand your organizational data. It’s used to view or create detailed business reports, analyze data, and help you make effective business decisions.
MicroStrategy is a business analytics platform that helps enterprises build and deploy analytics and mobile apps to transform their business. The MicroStrategy platform provides interactive dashboards, highly formatted reports, ad hoc queries, and automated report distribution. The software’s ROLAP architecture is a key differentiator from other vendors who offer full-featured solutions.
Palo OLAP Server
Palo is a MOLAP (Multidimensional Online Analytical Processing) server typically used as a BI tool for controlling and budgeting. It is a Jedox AG product. Palo enables multiple users to share one centralized data storage. It works with real-time data. Data can then be consolidated or written back with the help of multidimensional queries. Palo stores run-time data in its memory to give faster data access to users.
Sisense is an agile business intelligence (BI) solution that provides advanced tools to manage big data in marketing analytics. It helps you simplify complex data and transform it into powerful analytic apps to give you a more comprehensive understanding of your data.
icCube owns a business intelligence software that offers an end-to-end BI solution. This is great for software companies looking to embed data analytics, visualization, and reporting into their product.
icCube sells an online analytical processing server that is implemented in Java as per J2EE standards. It’s an in-memory OLAP server and is compatible with any data source that holds its data in tabular form.
SAP NetWeaver Business Warehouse
SAP NetWeaver Business Warehouse provides a high-performance infrastructure that helps you evaluate and interpret data. It provides reporting, analysis, and interpretation of business data quickly and in line with market needs.
Oracle Business Intelligence Enterprise Edition (OBIEE)
Oracle Business Intelligence Enterprise Edition helps customers discover new data insights and make faster business decisions by offering interactive dashboards, powerful operational reporting, and real-time alerts. It reduces the total cost of ownership and increases return on investment for the entire organization.
Apache Kylin is an open-source, distributed Analytical Data Warehouse for Big Data. It provides an SQL interface and MOLAP combined with Hadoop and Spark to support large data. In addition, Kylin reduces query processing time and quickly filters billions of data rows.
Businesses continuously need to plan, analyze, and report on sales and marketing activities to maximize efficiency. OLAP applications can help increase the productivity of business managers, developers, marketing analysts, and whole organizations. In addition, they can also help you transform data into actionable insights.
Take advantage of OLAP in marketing to analyze data accurately and quickly and turn it into actionable insights.