Business Intelligenz Schulungen

Business Intelligenz Schulungen

Business Intelligence (BI) training

Testi...Client Testimonials

Power BI

Offering a more in-depth scope about Power BI more than any training institute that i came across to.

Mohammed Al Ameer - BMMI

Power BI

Exercises, additional tips from the trainer, flexibility to add more insights when requested

Anna Alechno - British American Shared Services Europe BAT GBS Finance, WER/Centre/EEMEA

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Business Intelligenz Schulungsübersicht

Code Name Dauer Übersicht
fsharpfordatascience F# for Data Science 21 hours Data science is the application of statistical analysis, machine learning, data visualization and programming for the purpose of understanding and interpreting real-world data. F# is a well suited programming language for data science as it combines efficient execution, REPL-scripting, powerful libraries and scalable data integration. In this instructor-led, live training, participants will learn how to use F# to solve a series of real-world data science problems. By the end of this training, participants will be able to: Use F#'s integrated data science packages Use F# to interoperate with other languages and platforms, including Excel, R, Matlab, and Python Use the Deedle package to solve time series problems Carry out advanced analysis with minimal lines of production-quality code Understand how functional programming is a natural fit for scientific and big data computations Access and visualize data with F# Apply F# for machine learning Explore solutions for problems in domains such as business intelligence and social gaming Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
powerbi Power BI 14 hours Power BI Architecture Data sources On-premises and online data sources Data transformations + M language Direct connections to selected sources (SQL Server, OLAP) Modeling Relationship between tables (single and multidirectional data filtering) DAX - templates and best practices Introduction to DAX Most commonly used functions and context of calculations Working with the time dimension (including fiscal periods, comparing periods, YTD) Hierarchie parent-child Filtering data relative to hierarchy Popular DAX templates Visualizations Interactive data analysis Select the appropriate visualization Filters, grouping, exclusions Visualization on maps Visualizations using the R language Visualization enhancements (so-called custom visuals) Data Access Management - Row-Level Security Team work and mobile with Power BI Dashboards and reports Q & A mechanism Workspaces Mobile applications    
68780 Apache Spark 14 hours Why Spark? Problems with Traditional Large-Scale Systems Introducing Spark Spark Basics What is Apache Spark? Using the Spark Shell Resilient Distributed Datasets (RDDs) Functional Programming with Spark Working with RDDs RDD Operations Key-Value Pair RDDs MapReduce and Pair RDD Operations The Hadoop Distributed File System Why HDFS? HDFS Architecture Using HDFS Running Spark on a Cluster Overview A Spark Standalone Cluster The Spark Standalone Web UI Parallel Programming with Spark RDD Partitions and HDFS Data Locality Working With Partitions Executing Parallel Operations Caching and Persistence RDD Lineage Caching Overview Distributed Persistence Writing Spark Applications Spark Applications vs. Spark Shell Creating the SparkContext Configuring Spark Properties Building and Running a Spark Application Logging Spark, Hadoop, and the Enterprise Data Center Overview Spark and the Hadoop Ecosystem Spark and MapReduce Spark Streaming Spark Streaming Overview Example: Streaming Word Count Other Streaming Operations Sliding Window Operations Developing Spark Streaming Applications Common Spark Algorithms Iterative Algorithms Graph Analysis Machine Learning Improving Spark Performance Shared Variables: Broadcast Variables Shared Variables: Accumulators Common Performance Issues
3119 Business Intelligence mit MS SQL Server 2008 14 hours Training is dedicated to the basics of create a data warehouse environment based on MS SQL Server 2008. Course participant gain the basis for the design and construction of a data warehouse that runs on MS SQL Server 2008. Gain knowledge of how to build a simple ETL process based on the SSIS and then design and implement a data cube using SSAS. The participant will be able to manage OLAP database: create and delete database OLAP Processing a partition changes on-line. The participant will acquire knowledge of scripting XML / A and MDX. basis, objectives and application of data warehouse, data warehouse server types base building ETL processes in SSIS basic design data cubes in an Analysis Services: measure group measure dimensions, hierarchies, attributes, development of the project data cubes: measures calculated, partitions, perspectives, translations, actions, KPIs, Build and deploy, processing a partition the base XML / A: Partitioning, processes and overall Incremental, delete partitions, processes of aggregation, base MDX language
mdlmrah Model MapReduce und Apache Hadoop 14 hours The course is intended for IT specialist that works with the distributed processing of large data sets across clusters of computers. Data Mining and Business Intelligence Introduction Area of application Capabilities Basics of data exploration Big data What does Big data stand for? Big data and Data mining MapReduce Model basics Example application Stats Cluster model Hadoop What is Hadoop Installation Configuration Cluster settings Architecture and configuration of Hadoop Distributed File System Console tools DistCp tool MapReduce and Hadoop Streaming Administration and configuration of Hadoop On Demand Alternatives
JasperSoftBI JasperSoft BI 14 hours JasperReports is an open-source reporting library that can be embedded into any Java application. JasperReports Server is a Java EE web application with advanced reporting capabilities, including scheduling and permissions. In this instructor-led, live training, participants will learn to view and interact with business data as well as create and design reports and dashboards that are viewable on phones and tablets. By the end of this training, participants will be able to: Set up and configure a JasperSoft ETL project Design and run an ETL job Use iReport to generate charts, images, sub-reports, and cross tabs Audience BI analysts ETL developers Database professionals Format of the course Part lecture, part discussion, exercises and heavy hands-on practice   To request a customized course outline for this training, please contact us.  
TalendDI Talend Open Studio for Data Integration 28 hours Talend Open Studio for Data Integration is an open-source data integration product used to combine, convert and update data in various locations across a business. In this instructor-led, live training, participants will learn how to use the Talend ETL tool to carry out data transformation, data extraction, and connectivity with Hadoop, Hive, and Pig.   By the end of this training, participants will be able to Explain the concepts behind ETL (Extract, Transform, Load) and propagation Define ETL methods and ETL tools to connect with Hadoop Efficiently amass, retrieve, digest, consume, transform and shape big data in accordance to business requirements Audience Business intelligence professionals Project managers Database professionals SQL Developers ETL Developers Solution architects Data architects Data warehousing professionals System administrators and integrators Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.  
PentahoDI Pentaho Data Integration Fundamentals 21 hours Pentaho Data Integration is an open-source data integration tool for defining jobs and data transformations. In this instructor-led, live training, participants will learn how to use Pentaho Data Integration's powerful ETL capabilities and rich GUI to manage an entire big data lifecycle, maximizing the value of data to the organization. By the end of this training, participants will be able to: Create, preview, and run basic data transformations containing steps and hops Configure and secure the Pentaho Enterprise Repository Harness disparate sources of data and generate a single, unified version of the truth in an analytics-ready format. Provide results to third-part applications for further processing Audience Data Analyst ETL developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
magellan Magellan: Geospatial Analytics with on Spark 14 hours Magellan is an open-source distributed execution engine for geospatial analytics on big data. Implemented on top of Apache Spark, it extends Spark SQL and provides a relational abstraction for geospatial analytics. This instructor-led, live training introduces the concepts and approaches for implementing geospacial analytics and walks participants through the creation of a predictive analysis application using Magellan on Spark. By the end of this training, participants will be able to: Efficiently query, parse and join geospatial datasets at scale Implement geospatial data in business intelligence and predictive analytics applications Use spatial context to extend the capabilities of mobile devices, sensors, logs, and wearables Audience Application developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.  
zeppelin Zeppelin for interactive data analytics 14 hours Apache Zeppelin is a web-based notebook for capturing, exploring, visualizing and sharing Hadoop and Spark based data. This instructor-led, live training introduces the concepts behind interactive data analytics and walks participants through the deployment and usage of Zeppelin in a single-user or multi-user environment. By the end of this training, participants will be able to: Install and configure Zeppelin Develop, organize, execute and share data in a browser-based interface Visualize results without referring to the command line or cluster details Execute and collaborate on long workflows Work with any of a number of plug-in language/data-processing-backends, such as Scala ( with Apache Spark ), Python ( with Apache Spark ), Spark SQL, JDBC, Markdown and Shell. Integrate Zeppelin with Spark, Flink and Map Reduce Secure multi-user instances of Zeppelin with Apache Shiro Audience Data engineers Data analysts Data scientists Software developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.  
dashbuilderforengineers Dashbuilder for engineers 7 hours Dashbuilder is an open-source web application for visually creating business dashboards and reports. In this instructor-led, live training, participants will learn set up, configure, integrate and deploy Dashbuilder. By the end of this training, participants will be able to: Extract data from heterogeneous sources such as JDBC databases and text files Use connectors to connect to third-party systems and platforms such as jBPM     Configure roles, permissions and access controls for users Deploy Dashbuilder to a live production environment Audience Developers IT and system architects Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.  
dashbuilder Dashbuilder for business users 14 hours Dashbuilder is an open-source web application for visually creating business dashboards and reports. In this instructor-led, live training, participants will learn how to create business dashboards and reports using Dashbuilder. By the end of this training, participants will be able to: Visual configure and personalize dashboards using drag-and-drop Create different types of visualizations using charting libraries Define interactive report tables Create and edit inline KPIs (Key Performance Indicators) Customize the look and feel of metric displayers Audience Managers Analysts Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.  
kibana Kibana: Essentials 14 hours This training introduces Kibana to the users of Elastic Search. Kibana is an open source analytics and visualization platform designed to work with Elasticsearch. You use Kibana to search, view, and interact with data stored in Elasticsearch indices. You can easily perform advanced data analysis and visualize your data in a variety of charts, tables, and maps. Kibana makes it easy to understand large volumes of data. Its simple, browser-based interface enables you to quickly create and share dynamic dashboards that display changes to Elasticsearch queries in real time. Setting up Prerequisites Elasticsearch: Introduction  Elasticsearch: Installation and Configuration elasticdump Brief Introduction to Kibana Nested Objects - Limitation to Kibana Setting up Kibana Kibana: Install and Configure Configuring Elasticsearch and connecting Kibana Dynamic Mapping Limitations Tribe Nodes Using Kibana Indices and Filters Discover Interface Time Filter Toolbar and Searchbar Field Lists Document Data and Context - Add/View/Edit/Delete Visualization Interface Aggregations Bucket Aggregations - Date Histogram, Date Range, Range, Histogram, Terms and Filters Metric Aggregations - Count, Sum, Average, Min, Max, Percentile, Percentile Ranks and Unique Create Visualization Chart, Line, Area Data Table Metrics Other Visualization Types Dashboard Interface: Building, Merging, Loading and Sharing Graph: Configure, Troubleshoot and Limitations Kibana: Dev Console Overview Shortcuts: Brief Settings and Configuring Kibana in Production SSL encryption Load Balancing using Elasticsearch Nodes Management Managing Fields and Formatters Saved Searches, Visualizationad and Dashboards Apache/nginx proxy for security Plugins Install/Update/Disable/Remove Plugins Plugins Manager  
datameer Datameer for Data Analysts 14 hours Datameer is a business intelligence and analytics platform built on Hadoop. It allows end-users to access, explore and correlate large-scale, structured, semi-structured and unstructured data in an easy-to-use fashion. In this instructor-led, live training, participants will learn how to use Datameer to overcome Hadoop's steep learning curve as they step through the setup and analysis of a series of big data sources. By the end of this training, participants will be able to: Create, curate, and interactively explore an enterprise data lake Access business intelligence data warehouses, transactional databases and other analytic stores Use a spreadsheet user-interface to design end-to-end data processing pipelines Access pre-built functions to explore complex data relationships Use drag-and-drop wizards to visualize data and create dashboards Use tables, charts, graphs, and maps to analyze query results Audience Data analysts Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
deckgl deck.gl: Visualizing Large-scale Geospatial Data 14 hours deck.gl is an open-source, WebGL-powered library for exploring and visualizing data assets at scale. Created by Uber, it is especially useful for gaining insights from geospatial data sources, such as data on maps. This instructor-led, live training introduces the concepts and functionality behind deck.gl and walks participants through the set up of a demonstration project. By the end of this training, participants will be able to: Take data from very large collections and turn it into compelling visual representations Visualize data collected from transportation and journey-related use cases, such as pick-up and drop-off experiences, network traffic, etc. Apply layering techniques to geospatial data to depict changes in data over time Integrate deck.gl with React (for Reactive programming) and Mapbox GL (for visualizations on Mapbox based maps). Understand and explore other use cases for deck.gl, including visualizing points collected from a 3D indoor scan, visualizing machine learning models in order to optimize their algorithms, etc. Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.

Kommende Kurse

CourseSchulungsdatumKurspreis (Fernkurs / Schulungsraum)
Model MapReduce and Apache Hadoop - NürnbergMi, 2017-12-06 09:302010EUR / 2510EUR

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Business Intelligenz Schulung, Business Intelligenz boot camp, Business Intelligenz Abendkurse, Business Intelligenz Wochenendkurse , Business Intelligenz Lehrer , Business Intelligenz Training,Business Intelligenz Kurs, Business Intelligenz Seminare, Business Intelligenz Coaching, Business Intelligenz Seminar

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