Following the basic steps of the CRISP-DM (CRoss-Industry Standard Process for Data Mining) methdology, the course will introduce the basic models, tools and methods to do data-driven innovation.
During the Business Understanding task, you will be presented with different business scenarios that could benefit from data analytics. Data Understanding, will introduce you to the important aspects of data that should be considered for data-driven analytics solutions. During Data Preparation and Modelling, the course will introduce basic data preparation activities as required by analytics models, as well as a standard set of analytics models with their advantages. Evaluation and Deployment will introduce considerations when interpreting the results of analytic models, as well as how to deploy and refine analytics solutions into a business to support innovation.
After completion of the course, you should be able to:
a. understand how to use data for innovation and innovtaive solutions to business problems;
b. understand the CRISP-DM Phases and the activities within each phase;
c. understand what data understaning and preparation for data analytics entails;
d. be familiar with several analytics models, as well as their input and output requirements, how to prepare data for the models, as well as advantages and disadvantages of the models;
e. understand how to evaluate and deploy data analytics results to solve business problems and create new business opportunities;
f. be familiar with some of the ethical, legal and security aspects of data analytics;
g. be aware of existing popular data mining tools and packages.
The following will be covered during the training:
1) An Introduction to disruptive technologies impacting on businesses and organizations as well as the need for innovative data-driven solutions.
2) The CRISP-DM (CRoss-Industry Standard Process for Data Mining) methdology, as well as all the steps, task, activities and outputs generated during the phases of a data analytics project.
3) Business Understanding for analystics, including determining business objectives, assessing the situation, determining the data mining goals, and producing the project plan.
4) Data Understanding for analytics that includes initial data collection and insights into available sources of data, describing the data, exploration of the data and establishing the data quality of the data sources.
5) Data Preparation that includes all activities to construct the final data set or the data that will be fed into the modeling tool(s) from the initial raw data. Tasks include table, record, and attribute selection, as well as transformation and cleaning of data for modeling tools. This will also include hands-on exercises.
6) Modeling: various modeling techniques, including their parameters. Modeling steps include the selection of the modeling technique, the generation of test design, the creation of models and the assessment of models. Candidates will do practical exercises and use tools to deploy models.
7) Evaluation of models: Before proceeding to final deployment of the model, a thorough evaluation of the model and the reults are necessary in order to achieve the business objectives. Here it is critical to determine whether all business requirements gave been met, as well as how, and how to use the results.
8) Deployment of data mining results. It is important to ensure success by providing mechanisms that ensure that the knowledge gained is organized and presented in a useful way. This coulld be as simple as generating a report or as complex as implementing a repeatable data mining process across the enterprise.
9) Using data analytics to support innovation.
10) Ethical and security aspects of data mining and analytics, as well as legal requirements and responsibilities.
11) A quick overview of popular tools for data mining and analytics.
Information and Communication Technology
Who Should Attend:
Delegates in management and senior positions that want to understand how to exploit data analytics within the organization in order to create new and innovatove business opportunities and solutions.
Contact, Contact, Web Based