Analytics toolbox

SELECTION PATH OF ANALYTICAL MODEL

When solving a business question with the help of data, it is essential which analytical model is chosen. Each case to be solved requires a modelling system of its own kind and a certain set of variables. The question path of the attached diagram illustrates which models are suitable to be used in the case to be solved.

TECHNOLOGIES VOCABULARY

The storage, processing and use of data at a precise level require the right tools, databases and databanks. The range of various technologies related to the collection, storage, reporting, visualisation and analysis of data is wide, and new technologies and terms arise on a continuous basis. From the viewpoint of knowledge management, however, there are clear roles for the technologies used. For the vocabulary see below.

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ANALYTICS VOCABULARY

Advanced analytics refers to using data to explain phenomena that have taken place or to predict future events. While traditional reporting looks into history, modern analytical tools open a window to the future. Analytics is based on the use of mathematical models. The theoretical bases and uses of the models are varied. For the vocabulary see below.

 

Technologies vocabulary

API
AWS (Amazon Web Services)
Azure
Big Data
CDW
Data models
Database technologies
EDW (enterprise data warehouse)
ETL (extraction, transformation and loading)
GitHub
Hadoop
IaaS
IBM SPSS Modeler
Java
Javascript
Map reduce
Marketing automation
NodeJS
NoSQL (Not only SQL)
ODBC, JDBC (open database connectivity / java database connectivity)
PaaS
Python
R
Relational databases
SaaS
SAS
Spark
SQL
Web crawling

Analytics vocabulary

Algorithm
Association analyses
Bayesian methods
Business analytics
Business intelligence
Classification methods
Coefficient of determination
Confidence interval
Confounding variable
Control group
Correlation
Cross tabulation
Cross-over study design
Customer analytics
Data mining
Data science
Data synchronisation
Decision-making window
Dependent variable (response variable)
Descriptive analytics
Experimental design
Frequency distribution
Grouping methods (segmentation, clustering)
Hypothesis testing methods
Industrial internet (Internet of things)
Machine learning
Market basket analysis
Missing data
Moving average
Multivariate methods
Neural network
Noise
Optimisation (mathematical)
Outlier
Path analysis
Prediction model
Predictive analytics
Prescriptive analytics
Regression analysis
Root cause analysis
Sample
Scoring
Significance level
Simulation methods
Standard deviation
Survey
Survival analysis
Text analysis
Time series analysis
Variation coefficient
Web analytics

Predictive and Descriptive analytics
IBM SPSS Modeler
IBM SPSS Modeler Server
IBM SPSS Collaboration and Deployment Services

Optimization / Prescriptive analytics
IBM ILOG CPLEX Optimization Studio
IBM Decision optimization Center

Reporting and Business intelligence
IBM Cognos

Business planning
IBM Cognos TM1

IBM Predictive Customer Intelligence
IBM Predictive Maintenance and Quality
IBM Counter Fraud Management

Watson

WEX (Watson Explorer)

APIt

Bluemix

Softlayer