OLAP and Hadoop are not the same. OLAP is a technology to perform multi-dimensional analytics like reporting and data mining. It has been around since 1970. Hadoop is a technology to perform massive computation on large data. Around since 2002. They can be used together but there are differences when choosing between using Hadoop/MapReduce data […]
Posts Tagged ‘OLAP’
Migrating Essbase Cubes to Oracle Analytics Cloud
With the shift to the cloud, on-premises Essbase applications may be migrated to Oracle Analytics Cloud (OAC) using a simple method provided by Oracle. Essbase Life Cycle Management process is cost effective and easy to use utility for EPM Professional or Technical lead to migrate the applications to the cloud without the need of recreating […]
Druid – A Data Store to Support History and Real-time Analytics
As a part of Perficient big data practice, I have been working on identifying some open source data stores and search frameworks that enable the user to quickly query what he needs, and to process massive events/message stream, in addition to several frameworks such as Spark, ELK, Hadoop, HBase, Cassandra, I get to know about […]
Creating Dynamic OLAP cubes from Custom Field data, pt. 1
A source system that contains dynamic or customer-defined data fields is both an old problem and a sticky one in the DW/BI environment. A standard approach of flattening the dynamic data into name/value pairs is recommended for a relational-type database. But what about multidimensional modeling or OLAP storage? Name/value pairs are just the beginning. To […]
CFO Performance Insight – Déjà vu?
Recently, I attended the IBM Vision conference in Orlando. At the conference, I watched a presentation on what our friends at IBM are calling one of their “signature solutions”: CFO Performance Insight. This reminded me of various blog posts of mine, such as: Reengineering the Forecasting Process with Predictive Models (Nov 2nd 2012) and Forecasting […]