Before developing a course, we listen to the real needs and objectives of each client, to adjust training and get high profitability. We adjust each course to your needs.

We are also specialists in formations 'in company' tailored to the needs of each organization, where harvesting for several participants from the same company is much higher. If this is your case, contact us.

Check our courses

Intensive Sugar-Suite CRM

Intensive Sugar-Suite CRM

Goal

SugarCRM is a system for managing the customer relationship ( CRM ) based on LAMP (Linux -Apache -MySQL - PHP), developed by the company SugarCRM, Inc. located in Cupertino, California.

It has five editions, one free and four other issues with non-free components and a cost per user. SugarCRM is a complete CRM application for businesses of different sizes. It is designed to facilitate sales management, opportunities, business contacts and more. From version 4.5 lets you use SQL Server as a database; and the company has signed agreements with Microsoft to expand its market on Windows servers.

In Stratebi we specialize in implementing integrated CRM and Analytics Solutions, integrating Sugar CRM, CRM Suite, etc... with Pentaho.

Target audiences

Information technology professionals, IT managers, business analysts, systems analysts, Java architects, system developers, database administrators, developers and professionals in relation to the area of technology, marketing, business and financial.

Observations

Certification

All students receiving the course will be given a certificate of attendance.

Syllabus

First day

Introduction to SugarCRM - CRM Concepts
Installation and initial configuration
  • Preparing web server
  • MySQ server configuration
Introduction to administration
  • Admin page
  • Basic System Configuration
System users
  • Defining roles and permissions
  • Creating Users
Company Hierarchy

Second day

Sugar Studio
  • Tags
  • Campos
  • Views
  • Relations
  • subpanels
Module Loader
  • Themes, language
  • Other modules
  • SugarForge
Imports and exports
Best Practices

Dashboards and Scorecards

Dashboards and Scorecards

Goal

Dashboards are fully open and can integrate all kinds of external components : Google Maps, RSS news, Twitter, Facebook info, external sources, etc.

Dashboards are the great strategic tool for managers and analysts today.

They have become the most powerful to follow the progress of the company and the market competitive weapon , and react quickly and effectively.

In addition , by identifying the KPI (Key Performance Indicators) keys corporate organization Scorecards are implemented, following the methodology of Norton and Kaplan.

The aim is to teach students to build advanced methods Reporting and Dashboards data mining resources of a system on Pentaho Business Intelligence to analyze data from various sources and systems.

Target audiences

Professionals information technology, IT managers, business analysts, systems analysts, Java architects, system developers, database administrators, developers and professionals in relation to the area of technology, marketing, business and financial.

Observations

Os incluimos las principales claves para construir potentes Cuadros de Mando, del Curso de creación de Dashboards Open Source:


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Syllabus

Introduction Open Source Business Intelligence Platforms
  • Architecture and features of Pentaho, SpagoBI, BIRT, Mondrian, Kettle, Talend, etc.
  • Development Tools.
Introduction to Scorecards
Good practices in Dashboards
ScoreCards and Scorecards
Dashboards custom (Different technologies and examples)
CDF technologies and CDE
installation CDE
Working with CDE
  • Understanding Layouts components
  • Data Extraction (CDA Technology)
    • File structures
    • Kettle origin
    • Source Definition (JNDI)
    • MDX and SQL queries
  • Graphic elements
  • Parameterisation and dependencies
  • Interaction between graphical elements
  • advanced elements
    • Xactions
    • Integration of external graphics libraries
  • Applying CSS Styles
  • Javascripting
  • Export Dashboards
  • Dashboards for mobile devices
  • Advanced exercises

Power BI

Power BI

Goal

¡Aprende con los mejores, Stratebi es Partner Oficial de Microsoft Power BI en España!

Power BI es un conjunto de aplicaciones de análisis de negocios que permite analizar datos y compartir información. ¡Es la solución perfecta destinada a la inteligencia empresarial!

Conoce sus características técnicas

Con Power BI podrás crear potentes informes utilizando diferentes fuentes de datos: SAP HANA, MySQL, Teradata, IBM DB2, Dynamics Navision, CRM, SQL. Archivos de Excel, .CSV, JASON o descargar datos procedentes de servicios en línea como Facebook, Google Analytics, CRM de Salesforce, Marketo, MailChimp...

Stratebi es Partner de Microsoft PowerBi en España

¡Aprende a usarlo siempre estés donde estés!

PowerBI

 

Target audiences

Profesionales de las tecnologías de información, gestores de TI, Analistas de Negocio, Analistas de sistemas, arquitectos Java, desarrolladores de sistemas, administradores de bases de datos, desarrolladores y profesionales con relación a el área de tecnología, marketing, negocio y financiera.

Syllabus

Curso Online de Power BI

  •  Online

Fecha: Del 17 de feb. al 18 de feb. de 2021

Horario: 15:00 h - 21:00 h ( CEST - Madrid)

Lugar: Plataforma web con profesor

Precio: 95 € (iva no incluido)  / persona 

Pago: PayPal o Trans. Bancaria (Consultar)

Certificado: Entrega a todos los asistentes

 

 

 

1. Introducción a concepto de Business Intelligence

2. Análisis de fuentes de datos

3. Introducción a Power BI

  • Entorno de trabajo: Power BI Desktop
  • Componentes: Power BI Desktop y Power BI Servicio Cloud
  • Tareas: Conectar, integrar, modelar y visualizar
  • Cuadros de mando (Paneles) e informes
  • Funcionalidades del entorno Power BI
  • Paquetes de contenido y aplicaciones

4. Conectar

  • Editor de consultas de Power BI
  • Extracción de datos: Extracción vs Direct Query
  • Conectar datos alojados en diferentes orígenes
  • Realizar transformaciones básicas sobre los datos en la consulta
  • Enlazar datos desde la consulta

5. Modelar

  • Entorno de trabajo para modelar con Power BI
  • Introducción al modelado tabular con Power BI
  • Tablas y relaciones
  • Introducción a fórmulas DAX
  • Columnas calculadas y medidas
  • Tablas calculadas
  • Fórmulas DAX de inteligencia de tiempo (YTD, MTD, PreviousQuarter, …)

6. Visualizar

  • Entorno de trabajo para creación de gráficos con Power BI
  • Trabajar con distintos tipos de gráficos
  • Formatos para gráficos e informes
  • Visualización de información geográfica en Mapas de Bing y ArcGIs de Esri
  • Importación de visualizaciones extra desde el Office Store / AppSource

7. Conectividad Y Colaboración

  • Aplicaciones en el Servicio de Power BI
  • Power BI Mobile (Alertas, suscripciones y favoritos)

Machine Learning

Machine Learning

Goal

This course will understand the concepts needed to perform processes Machine Learning, this branch of artificial intelligence that aims to develop techniques that allow computers to learn.

Machine Learning projects create algorithms that can generalize and recognize behavior patterns from information provided by way of example ( training). Machine Learning techniques are used among others in the following areas: Medicine, Bioinformatics, Marketing, Natural Language Processing, Image Processing, Machine Vision, Spam Detection.

Machine Learning

Target audiences

  • ICT professionals: Consultants BI, Scientific Data.
  • Professionals of Applied Sciences: Mathematics, Statistics, Physics.

Observations

  • Methodology: The course intersperses theoretical parts where fundamental concepts are taught to understand the practical exercises taught.
  • Requirements: Basics: Linear Algebra, calculus and probability theory.
 

Syllabus

Machine Learning with Scikit-Learn Data Science framework (Anaconda with Python 3)

1. Introduction to Machine Learning

  • Techniques
    • Classification
    • Regression
    • Clustering
  • Preprocessing and dimensional reduction
  • Attribute selection
  • Performance evaluation
    • Matrices de confusión
    • KPIs R2, MAE, MSE

2. Regression (Prediction of continuous values)

  • Algorithms 
    • Ordinal Least Squares
    • Ridge Regression
    • Laso Regression
    • Elastic Net
  • Examples

3. Classification (Identification of the category to which an object belongs)

  • Algorithms 
    • Logistic Regression
    • Support Vector Machines
    • KNearest Neighbors
    • Decision Trees
    • Random Forest
    • Multi-layer Perceptron
  • Examples

4. Clustering (Grouping similar objects in sets)

  • Algorithms
    • KMeans
    • Spectral Clustering
    • DBSCAN
  • Examples

Contacto

Ajustamos cada curso a sus necesidades.

Nuestra oficina en Madrid

Do you need a training?. We may offer a wide training catalog based on platform and software tools such as Pentaho, Talend, Mondrian, Ctools.