Business Intelligence Training in Clermont-Ferrand

Online or onsite, instructor-led live Business intelligence (BI) training courses demonstrate through hands-on practice how to understand, plan and implement BI within an organization.

BI training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Clermont-Ferrand onsite live Business Intelligence trainings can be carried out locally on customer premises or in NobleProg corporate training centers.

NobleProg -- Your Local Training Provider

Image of NobleProg Training Place, City Clermont-Ferrand, ZI Le Brézet

NobleProg Clermont-Ferrand, 34, Rue Jules Verne , Clermont-Ferrand, france, 63000

Training courses can be organised at our premises in Clermont-Ferrand, at your premises, or remotely. Training courses are given in English or French. We organise a coordination meeting with the trainer and the participants to adapt the training program to your expectations. The courses consist of interactive discussions, theoretical parts and practical exercises. The training is available as "live on-site training" or "live remote training". Live on-site training can be conducted locally at the client's premises in Clermont or at the NobleProg corporate training centers in Clermont-Ferrand. Remote e-learning is conducted using an interactive desktop computer. NobleProg is the publisher of the DaDesktop software, which is presented in a video at https://www.dadesktop.com/

Subcategories (17)

Explore Our Courses

Artificial Intelligence for Data Analysis in the Financial Sector

28 Hours

QuickSight Dashboard Authoring and Administration

14 Hours

Business Intelligence Reporting Tool (BIRT)

14 Hours

Oracle Business Intelligence (OBI)

28 Hours

SAS Business Intelligence (BI)

28 Hours

SAP BusinessObjects Business Intelligence (BI)

28 Hours

Advanced Data Integration and Visualization with Looker Studio

14 Hours

Cognos Analytics for Finance: Certification Preparation

28 Hours

Excel and Google Sheets

14 Hours

Sisense Business Intelligence

14 Hours

Comprehensive Splunk Administration and Advanced Utilization

28 Hours

Advanced JasperReports

14 Hours

Alteryx Advanced

14 Hours

AWS QuickSight

14 Hours

Cognos 11

14 Hours

Google Sheets for Excel Users

14 Hours

Getting Started with Looker Studio

14 Hours

MicroStrategy for Architects

14 Hours

Splunk Fundamentals 2

14 Hours

Statistical Analysis with Stata and Integration with R

35 Hours

Apache Superset for Administrators

28 Hours

Business Intelligence in MS SQL Server 2008

14 Hours

Advanced Splunk

14 Hours

Advanced Apache Superset

14 Hours

Algorithmic Trading with Python and R

14 Hours

Alteryx for Data Analysis

7 Hours

Alteryx for Developers

14 Hours

Big Data Business Intelligence for Govt. Agencies

35 Hours

Advances in technologies and the increasing amount of information are transforming how business is conducted in many industries, including government. Government data generation and digital archiving rates are on the rise due to the rapid growth of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals. As digital information expands and becomes more complex, information management, processing, storage, security, and disposition become more complex as well. New capture, search, discovery, and analysis tools are helping organizations gain insights from their unstructured data. The government market is at a tipping point, realizing that information is a strategic asset, and government needs to protect, leverage, and analyze both structured and unstructured information to better serve and meet mission requirements. As government leaders strive to evolve data-driven organizations to successfully accomplish mission, they are laying the groundwork to correlate dependencies across events, people, processes, and information. High-value government solutions will be created from a mashup of the most disruptive technologies:

Mobile devices and applications
Cloud services
Social business technologies and networking
Big Data and analytics

IDC predicts that by 2020, the IT industry will reach $5 trillion, approximately $1.7 trillion larger than today, and that 80% of the industry's growth will be driven by these 3rd Platform technologies. In the long term, these technologies will be key tools for dealing with the complexity of increased digital information. Big Data is one of the intelligent industry solutions and allows government to make better decisions by taking action based on patterns revealed by analyzing large volumes of data — related and unrelated, structured and unstructured. But accomplishing these feats takes far more than simply accumulating massive quantities of data.“Making sense of thesevolumes of Big Datarequires cutting-edge tools and technologies that can analyze and extract useful knowledge from vast and diverse streams of information,” Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy wrote in a post on the OSTP Blog. The White House took a step toward helping agencies find these technologies when it established the National Big Data Research and Development Initiative in 2012. The initiative included more than $200 million to make the most of the explosion of Big Data and the tools needed to analyze it. The challenges that Big Data poses are nearly as daunting as its promise is encouraging. Storing data efficiently is one of these challenges. As always, budgets are tight, so agencies must minimize the per-megabyte price of storage and keep the data within easy access so that users can get it when they want it and how they need it. Backing up massive quantities of data heightens the challenge. Analyzing the data effectively is another major challenge. Many agencies employ commercial tools that enable them to sift through the mountains of data, spotting trends that can help them operate more efficiently. (A recent study by MeriTalk found that federal IT executives think Big Data could help agencies save more than $500 billion while also fulfilling mission objectives.). Custom-developed Big Data tools also are allowing agencies to address the need to analyze their data. For example, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. The system has helped medical researchers find a link that can alert doctors to aortic aneurysms before they strike. It’s also used for more mundane tasks, such as sifting through résumés to connect job candidates with hiring managers.

Big Data Business Intelligence for Telecom and Communication Service Providers

35 Hours

Overview Communications service providers (CSP) are facing pressure to reduce costs and maximize average revenue per user (ARPU), while ensuring an excellent customer experience, but data volumes keep growing. Global mobile data traffic will grow at a compound annual growth rate (CAGR) of 78 percent to 2016, reaching 10.8 exabytes per month. Meanwhile, CSPs are generating large volumes of data, including call detail records (CDR), network data and customer data. Companies that fully exploit this data gain a competitive edge. According to a recent survey by The Economist Intelligence Unit, companies that use data-directed decision-making enjoy a 5-6% boost in productivity. Yet 53% of companies leverage only half of their valuable data, and one-fourth of respondents noted that vast quantities of useful data go untapped. The data volumes are so high that manual analysis is impossible, and most legacy software systems can’t keep up, resulting in valuable data being discarded or ignored. With Big Data & Analytics’ high-speed, scalable big data software, CSPs can mine all their data for better decision making in less time. Different Big Data products and techniques provide an end-to-end software platform for collecting, preparing, analyzing and presenting insights from big data. Application areas include network performance monitoring, fraud detection, customer churn detection and credit risk analysis. Big Data & Analytics products scale to handle terabytes of data but implementation of such tools need new kind of cloud based database system like Hadoop or massive scale parallel computing processor ( KPU etc.) This course work on Big Data BI for Telco covers all the emerging new areas in which CSPs are investing for productivity gain and opening up new business revenue stream. The course will provide a complete 360 degree over view of Big Data BI in Telco so that decision makers and managers can have a very wide and comprehensive overview of possibilities of Big Data BI in Telco for productivity and revenue gain. Course objectives Main objective of the course is to introduce new Big Data business intelligence techniques in 4 sectors of Telecom Business (Marketing/Sales, Network Operation, Financial operation and Customer Relation Management). Students will be introduced to following:

Introduction to Big Data-what is 4Vs (volume, velocity, variety and veracity) in Big Data- Generation, extraction and management from Telco perspective
How Big Data analytic differs from legacy data analytic
In-house justification of Big Data -Telco perspective
Introduction to Hadoop Ecosystem- familiarity with all Hadoop tools like Hive, Pig, SPARC –when and how they are used to solve Big Data problem
How Big Data is extracted to analyze for analytics tool-how Business Analysis’s can reduce their pain points of collection and analysis of data through integrated Hadoop dashboard approach
Basic introduction of Insight analytics, visualization analytics and predictive analytics for Telco
Customer Churn analytic and Big Data-how Big Data analytic can reduce customer churn and customer dissatisfaction in Telco-case studies
Network failure and service failure analytics from Network meta-data and IPDR
Financial analysis-fraud, wastage and ROI estimation from sales and operational data
Customer acquisition problem-Target marketing, customer segmentation and cross-sale from sales data
Introduction and summary of all Big Data analytic products and where they fit into Telco analytic space
Conclusion-how to take step-by-step approach to introduce Big Data Business Intelligence in your organization

Target Audience

Network operation, Financial Managers, CRM managers and top IT managers in Telco CIO office.
Business Analysts in Telco
CFO office managers/analysts
Operational managers
QA managers

Big Data Business Intelligence for Criminal Intelligence Analysis

35 Hours

Cluster Analysis with R and SAS

14 Hours

Data Preparation with Alteryx

7 Hours

Apache Druid for Real-Time Data Analysis

21 Hours

IBM Cognos Analytics

14 Hours

JasperReports

14 Hours

Business Intelligence and Data Analysis with Metabase

14 Hours

MicroStrategy Business Intelligence (BI)

14 Hours

MicroStrategy for Developers

14 Hours

Power BI Dashboards

14 Hours

Pentaho Open Source BI Suite Community Edition (CE)

28 Hours

Qlik Sense for Data Science

14 Hours

QlikView for Business Users

7 Hours

QlikView for Developers

14 Hours

Data Analysis with Redash

14 Hours

SAS Programming

14 Hours

Splunk Fundamentals

14 Hours

Splunk Data Administration

14 Hours

Business Intelligence with SSAS

14 Hours

Stata: Beginner to Advanced

14 Hours

Statistical Analysis with Stata and R

35 Hours

Getting Started with Apache Superset

14 Hours

Last Updated: 2025-04-16

Testimonials (25)

Deepthi was super attuned to my needs, she could tell when to add layers of complexity and when to hold back and take a more structured approach. Deepthi truly worked at my pace and ensured I was able to use the new functions /tools myself by first showing then letting me recreate the items myself which really helped embed the training. I could not be happier with the results of this training and with the level of expertise of Deepthi!

Deepthi - Invest Northern Ireland

Course - IBM Cognos Analytics

The diversity of topics covered

Romaric - Vacher

Course - Business Intelligence and Data Analysis with Metabase

Machine Translated

The ability of the trainer to align the course with the requirements of the organization other than just providing the course for the sake of delivering it.

Masilonyane - Revenue Services Lesotho

Course - Big Data Business Intelligence for Govt. Agencies

The content was tough but that extra effort I had to put helped me remember and understand power BI better.

Melvin - TLI Group

Course - Power BI DAX Fundamentals

The energy, knowledge and style of teaching of the trainer

Ioana - MOLSONCOORS GLOBAL BUSINESS SERVICES SRL

Course - From Tableau Beginners to Advanced User

The course material was commendable, featuring insightful overviews of Linux and Superset. While the Python component was comprehensive, it demanded a substantial coding proficiency

EMMANUEL MFANA KUNENE - Palladium Group

Course - Apache Superset for Administrators

lots of pratical exercises

Marcin - Narodowy Bank Polski

Course - Splunk Data Administration

Discussing about our issues

Rr Dwi Putri Periska Sari - PT. Becton Dickinson Indonesia

Course - Power BI for Developers

Data management, reporting and statistics concepts.

Dumisani - Interfront SOC Ltd

Course - Stata: Beginner to Advanced

Weronika created a really friendly, informal atmosphere. The training involved a lot of useful knowledge transfer, technical skills exercises and theory, as well as best practices and guidance on how to handle our own data.

Julia Kuczma - DLA Piper GSC Poland Sp. z o.o.

Course - Tableau Intermediate Training Course

What I liked the most was the coach's openness regarding the change in content as well as the approach that was previously prepared to accommodate our real needs

Ernesto Sitoe Junior - Electricidade de Mocambique

Course - Advanced Power BI

Understanding big data beter

Shaune Dennis - Vodacom

Course - Big Data Business Intelligence for Telecom and Communication Service Providers

I liked the fact that it was very dynamic, adjusted to our needs.

Bogdan Dinica - Sennheiser Consumer Electronics GmbH, Brasov Division

Course - MicroStrategy Business Intelligence (BI)

Younes is a great trainer. Always willing to assist, and very patient. I will give him 5 stars. Also, the QLIK sense training was excellent, due to an excellent trainer.

Dietmar Glanninger - BMW

Course - Qlik Sense for Data Science

Hands on exercise and the guidance of the trainer

Jackielou Nina Dellosa - Asiagate Networks, Inc.

Course - JasperReports

Share example of application

Course - Alteryx for Data Analysis

Very clearly articulated and explained

Harshit Arora - PwC South East Asia Consulting

Course - Alteryx for Developers

Labs, they were very interesting.

Aurora Sanz - ITALTEL SA

Course - Splunk Fundamentals

The second day as Power Bi is a really friendly tool, and clearly Costas knows it very well, it was really good to learn about that tool. Unfortunately we have to see Power pivot in excel first which is really not user friendly but definitely a must see first in order to understand how Power Bi works, and it makes Power Bi look super cool :)

Anne-Cecile Jacquot - Ameropa

Course - Excel to Power BI

Linear regression - the algorithm to predict the trend

Vincent Ko - UBS

Course - Data Preparation with Alteryx

The trainer answered all of my questions and gives us a walkthrough.

Mark Xavier Rimas - AIGSS- BPI

Course - Tableau Fundamentals to Advanced

The easy rapport with Gunnar was really helpful in learning the topic(s). There was little to no pressure to follow along perfectly with examples as can happen in some classes. He was very supportive and would happily retrace our steps and figure out the issue. Being the only person in the class allowed me to also ask a lot of questions of Gunnar. It was a very informative class.

Karen Salamy - Monterey Bay Aquarium Research Institute (MBARI)

Course - Getting Started with Apache Superset

Setting up the universal forwarder and heavy forwarder is something I know for a fact I will use on my team.

Madison Sample - Ultimate Knowledge

Course - Advanced Splunk

The second day was very interesting. It was a good training to see some possibilities within Power BI; but mostly you learn then while you work with Power BI. Fact is also that the training base has all access rights and everything works, but as soon as you try to connect to the live system, it does not work and this makes the knowledge transfer a bit difficult.

Marco Iuliano

Course - Power BI Dashboards

The knowledge of trainor about the tool.

Kendrick Bacani - Thakral One Inc.

Course - Data analysis with Tableau