What is OLAP?

Summary

In this informative video, Jared Hillam explores the decision-making process behind implementing OLAP (Online Analytical Processing) in business intelligence. He explains the history of OLAP, its benefits like instant data analysis through pre-processed combinations of dimensions and measures, and its challenges, such as reliance on IT for structural changes and the difficulty of managing too many dimensions. Hillam introduces the Dimensional Relational Model as a flexible alternative and suggests that OLAP can complement this model in structured environments like finance. He concludes by emphasizing the importance of a balanced solution tailored to an organization's needs.

Takeaways

• 📚 OLAP stands for Online Analytical Processing, a technology designed to facilitate fast and flexible querying of data in business environments.
• 🕵️‍♂️ OLAP was introduced in response to the difficulties businesses faced in querying data from relational databases in the 90s, which were slow and inflexible.
• 🛠️ A critical goal of OLAP is to minimize on-the-fly processing by pre-processing and storing every possible combination of dimensions, measures, and hierarchies for quick data access.
• 🔧 OLAP faces challenges such as reliance on IT for managing changes to the OLAP structure, which can hinder flexibility in data analysis.
• 🏢 OLAP is highly accepted in structured analytical environments like Finance and Accounting, but may not be as suitable for areas requiring more freedom in data analysis.
• 🤔 The success of OLAP implementations requires close collaboration between IT and business units, as IT needs to anticipate user data paths, which is challenging without foresight.
• 🧩 Balancing the number of dimensions in OLAP is crucial; too many can confuse users, while too few limit data analysis capabilities.
• 🧐 Humans typically struggle with understanding more than three dimensions, and more than seven dimensions are considered overwhelming.
• 🔄 An alternative to OLAP is the Dimensional Relational Model, which optimizes data for live queries rather than pre-calculating all combinations.
• 🆓 The Dimensional Relational Model offers greater flexibility by allowing users to select dimensions for analysis without pre-calculating permutations.
• 🔗 OLAP can complement the Dimensional Relational Model, particularly in highly structured analysis paths like finance and accounting.
• 🌐 Intricity specializes in building information infrastructure and can guide organizations to a balanced solution that optimizes decision-making investments.

Q & A

What is OLAP and why was it introduced?

OLAP stands for Online Analytical Processing. It was introduced in the mid to late 90's to address the difficulties businesses faced in querying data from their relational databases. OLAP aimed to minimize on-the-fly processing by pre-processing and storing every possible combination of dimensions, measures, and hierarchies to allow for fast and flexible data navigation.

What are the main goals of OLAP vendors?

The main goals of OLAP vendors are to minimize the amount of on-the-fly processing needed during data navigation and to provide a system that allows data to appear instantaneously when users investigate the information.

Why might OLAP be less suitable for certain business environments?

OLAP might be less suitable for environments that require a lot of freedom to analyze data due to its reliance on IT to manage any changes to the OLAP structure. This can make it challenging in areas like Sales, Operations, Marketing, and R&D.

Which business areas typically have a high acceptance rate for OLAP?

OLAP has a high acceptance rate in very structured analytical environments like Finance and Accounting.

What is the relationship between IT departments and the success of OLAP implementation?

IT departments play a crucial role in the success of OLAP implementation. They need to have a close relationship with the business to precisely determine not just what data is needed, but also what path the user might take with the data.

What are the challenges faced in balancing the number of dimensions in an OLAP structure?

The challenges include avoiding confusion with too many dimensions and ensuring there are enough dimensions to work with the data effectively. OLAP cubes pre-calculate all resulting combinations between dimensions, but humans have difficulty understanding more than three dimensions, making more than seven dimensions too much to keep track of.

What is a Dimensional Relational Model and how does it differ from OLAP?

A Dimensional Relational Model is a data model that does not pre-calculate every possible combination of dimensions. Instead, it stores data optimized for live queries, allowing for greater flexibility and control by the end user. Unlike OLAP, it does not require pre-calculation of all permutations ahead of time.

How can a Dimensional Relational Model offer more flexibility than OLAP?

A Dimensional Relational Model offers more flexibility by processing data at run time, allowing end users to select the dimensions they want to see without pre-calculating all their permutations. This provides the ability to handle a larger number of dimensions and puts users in control of their data requests.

Can OLAP be used in conjunction with a Dimensional Relational Model?

Yes, OLAP can be a complementary solution to a Dimensional Relational Model, especially in cases like finance and accounting where there is a highly structured analysis path. Cubes can be created from the data stored in Dimensional Relational Models.

What role does Intricity specialize in regarding information infrastructure?

Intricity specializes in helping organizations build the right information infrastructure. They have a deep understanding of the tactical, strategic, and cultural impacts of different solutions and can guide organizations to a balanced solution that maximizes their investments in making better decisions.

How can someone get in touch with Intricity's specialists for further guidance?

To get in touch with Intricity's specialists, one can visit their website and engage in a conversation to receive guidance towards a balanced solution for their information infrastructure needs.