Business Intelligence (BI) in Python, OLAP
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Updated
Dec 2, 2016 - Python
Business Intelligence (BI) in Python, OLAP
Sparkline BI Accelerator provides fast ad-hoc query capability over Logical Cubes. This has been folded into our SNAP Platform(https://bit.ly/2oBJSpP) an Integrated BI platform on Apache Spark.
A Simple and Efficient Distributed Multidimensional BI Analysis Engine.
TinyOlap is a light-weight, in-process, in-memory, multi-dimensional, model-first OLAP engine for planning, budgeting, reporting, analysis and many other numerical purposes, written in plain Python.
is an hypercube of data
This is a business intelligence project on analyzing super market data. Check out the README file for more details.
Official JavaScript client for SlicingDice, Data Warehouse and Analytics Database as a Service.
Build and deploy automated to SQL Server Analysis Services (SSAS) with Python.
SQL Server Analysis Services multidimensional databases metadata reader
Open Mining Language (OML), language to preprocess Olap Cubes
A project which implements the Data Science pipeline - Extracting raw data, Data Cleaning, Feature Extraction, Entity Matching, Data Matching, Data Merging and OLAP style exploration. The two entities chosen are Yelp and Zomato. Restaurant data from the same localities will be extracted from both sites and similar restaurants will be merged into…
SQL script to create and populate a date dimension which is used in generating OLAP Cubes. Also a function to convert dates from Gregorian to Jalali calendar (A.K.A Persian calendar)
Board games analysis & Tableau visualizations. 🎲
Docker image for Druid.io's Tranquility event-stream processing server
A blockchain enabled OLAP Data Warehouse. It is the implementation / application part of my thesis as an undergraduate Computer Science student of Athens University of Economics and Business
PoC using OpenAI API via LangChain to create SPARQL queries that query RDF cubes
Official Go client for SlicingDice, Data Warehouse and Analytics Database as a Service.
The Data Warehouse and Business Intelligence Project. Cleaned analyzed and stored a Meal Deman Forcasting data set to a Datawarehouse using ETL processing. OLAP operations were performed by SSAS cube deployment using SQL Server data tools. As the next part of the project, data visualization using Excel power view, pivot charts and pivot tables w…
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