Business Intelligence Training in Tunisia

Power BI is a business intelligence tool by Microsoft that enables real-time data integration, visualization, and analysis across multiple data sources, including BIM platforms.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to implement Power BI for data retrieval and analysis from multiple databases and BIM models, using AI tools for trend detection and reporting.

By the end of this training, participants will be able to:

• Implement Power BI for real-time data integration.
• Retrieve and analyze data from multiple databases and BIM sources.
• Create visual reports using AI-supported trend analysis.
• Integrate BIM data models for technical and managerial insights.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Tunisia (online or onsite) is aimed at intermediate-level data professionals who wish to learn how to use Datameer to prepare, analyze, and visualize data using modern techniques, guided workflows, and the latest Datameer interface.

By the end of this training, participants will be able to:

• Create and manage data projects within Datameer's workspace.
• Connect to modern data platforms including Snowflake, cloud storage, and databases.
• Perform data transformation using visual, code-free workflows or SQL.
• Collaborate with teams using metadata management and project sharing.
• Use visual exploration tools to profile and understand datasets.
• Create and share rich data visualizations and dashboards.

This instructor-led, live training in Tunisia (online or onsite) is aimed at beginner-level financial analysts who wish to integrate AI effectively into their data analysis processes.

By the end of this training, participants will be able to:

• Understand the application of AI in data analysis specific to the financial industry.
• Develop skills to build predictive and prescriptive models for financial analysis.
• Learn how to implement machine learning algorithms for financial data processing.
• Enhance data visualization and interpret complex AI-driven insights for decision-making.

This instructor-led, live training in Tunisia (online or onsite) is aimed at intermediate-level data and business analysts who wish to create, manage, and administer dashboards using Amazon QuickSight.

By the end of this training, participants will be able to:

• Understand the benefits, use cases, and key features of Amazon QuickSight.
• Learn to connect QuickSight to multiple data sources and author interactive data visualizations and dashboards.
• Apply security and access controls in QuickSight.
• Utilize machine learning capabilities built into QuickSight for enhanced data insights.
• Design, create, and customize QuickSight dashboards to extract and visualize business insights.

This instructor-led, live training in Tunisia (online or onsite) is aimed at intermediate-level data and business analysts who wish to use BIRT to effectively create and deploy business intelligence reports.

By the end of this training, participants will be able to:

• Understand the architecture and components of the BIRT framework.
• Design and create informative, dynamic reports using BIRT Report Designer.
• Use BIRT’s scripting capabilities to add business logic to reports.
• Optimize and deploy BIRT reports within web applications and standalone applications.

This instructor-led, live training in Tunisia (online or onsite) is aimed at beginner-level business analysts and data analysts who wish to leverage Oracle BI to extract valuable insights from their data.

By the end of this training, participants will be able to:

• Navigate and utilize the Oracle BI interface effectively.
• Create and customize reports and dashboards tailored to business needs.
• Conduct ad-hoc analysis using various BI tools.
• Utilize advanced features for comprehensive data exploration.

This instructor-led, live training in Tunisia (online or onsite) is aimed at beginner-level business analysts and data analysts who wish to harness the power of SAS BI to extract meaningful insights from data.

By the end of this training, participants will be able to:

• Navigate and utilize the SAS BI interface effectively.
• Create customized reports and dashboards tailored to business needs.
• Conduct ad-hoc analysis using various BI tools.
• Leverage advanced features for comprehensive data exploration.

This instructor-led, live training in Tunisia (online or onsite) is aimed at beginner-level business analysts and data analysts who wish to acquire essential skills in using SAP BusinessObjects BI to transform raw data into meaningful insights.

By the end of this training, participants will be able to:

• Navigate and use the SAP BusinessObjects BI interface.
• Create and customize business reports and dashboards.
• Perform ad-hoc analysis using various BI tools.
• Utilize advanced features for in-depth data exploration.

This instructor-led, live training in Tunisia (online or onsite) is aimed at developers and system administrators who wish to learn and use Sisense for big data manipulation and visualization.

By the end of this training, participants will be able to:

• Learn the fundamental concepts of Sisense and how it works.
• Create a Sisense dashboard to visualize big data and execute data-driven business decisions.
• Merge and manage data from multiple sources.
• Utilize Sisense for quick data manipulation and visualization.

This instructor-led, live training in Tunisia (online or onsite) is aimed at data scientists and data analysts who wish to learn how to use each tool in the developer tool palette in Alteryx Designer.

By the end of this training, participants will be able to:

• Learn to use and configure all the tools in the developer tab.
• Design efficient workflows in Alteryx using the dynamic, validation, and testing tools.
• Learn how to use API tools to download and parse web data.
• Use Alteryx scripting tools, including Python and R.

This instructor-led, live training in Tunisia (online or onsite) is aimed at data analysts or anyone who wishes to use AWS QuickSight data analysis and visualization.

By the end of this training, participants will be able to:

• Understand the basic concepts of AWS QuickSight.
• Use AWS QuickSight to create data analysis, reports, and insights.
• Use AWS to create relationships between data for enhanced analysis.
• Learn different types of visualizations in understanding data.

This instructor-led, live training in Tunisia (online or onsite) is aimed at data analysts who wish to use Google Sheets for data analysis.

By the end of this training, participants will be able to:

• Build spreadsheets with Google Sheets.
• Use formulas that work both in Google Sheets and Excel.
• Format and analyze any data.
• Create data visualizations with charts and graphs.

This instructor-led, live training in Tunisia (online or onsite) is aimed at beginner-level to intermediate-level participants who wish to build foundational skills for data visualization and reporting using Looker Studio, and learn how to connect data sources, visualize information effectively, and gain actionable insights.

By the end of this training, participants will be able to:

• Understand the core features of Looker Studio and its use cases.
• Set up Looker Studio and connect to various data sources.
• Create engaging dashboards with charts, graphs, and filters.
• Customize reports for specific audiences and business needs.
• Collaborate on and share dashboards effectively.

This instructor-led, live training in Tunisia (online or onsite) is aimed at beginner to advanced-level MicroStrategy architects who wish to develop schemas, change management, and use modeling tools to manage the development cycle of MicroStrategy apps.

By the end of this training, participants will be able to:

• Fully understand the concepts and architecture of data warehousing.
• Understand how to use analytics, desktop objects, and schemas.
• Build and maintain MicroStrategy projects.

This instructor-led, live training in Tunisia (online or onsite) is aimed at data analysts who wish to learn techniques for preparing data in Excel, then visualizing it in Power BI.

By the end of this training, participants will be able to:

• Understand the principles of data analysis, objectives of data analysis, and approaches for data analysis.
• Use DAX formulas in Power BI for complex calculations.
• Create and use visualizations and charts for particular analysis cases.
• Import with Power View to move from Excel based Power BI to independent Power BI.

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.

This instructor-led, live training in Tunisia (online or onsite) is aimed at data analysts, data scientists and data engineers who wish to carry out advanced data analytics and visualization using Apache Superset.

By the end of this training, participants will be able to:

• Install and configure Apache Superset.
• Implement advanced data analysis and visualization using Apache Superset.
• Customize and share dashboards and reports.
• Managing security in Apache Superset.

The "Big Data and AI in Banking" training program is designed to equip professionals in the banking industry with essential skills and knowledge to harness the power of Big Data and artificial intelligence. Participants will explore foundational concepts, technologies, and practical applications of Big Data and AI within the banking sector. The training will encompass a blend of theoretical instruction, case studies, hands-on sessions, and discussions on regulatory implications, ethical considerations, and best practices. 

By the end of this training, participants will be able to:

1. Understand Key Concepts: Provide participants with a foundational understanding of Big Data and AI, including their significance in the banking sector. 
2. Explore Technologies: Familiarize attendees with core Big Data technologies, including Hadoop and Spark, and the relevance of NoSQL databases. 
3. Leverage Data Sources: Teach participants to identify and utilize various internal and external data sources for effective banking operations. 
4. Applications of AI: Illustrate the use of AI techniques in bank examinations, such as risk assessment, fraud detection, and predictive modeling. 
5. Implement Data Analytics: Equip participants with the skills to apply data analytics methods for trend identification and risk management in banking contexts 
6. Address Ethical Considerations: Discuss the ethical implications of using Big Data and AI in banking and the importance of compliance with regulations 
7. Prepare for Future Trends: Prepare participants to navigate future innovations in technology and develop strategies for the integration of Big Data and AI into banking practices 

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.

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

In this instructor-led, live training in Tunisia, participants will learn the mindset with which to approach Big Data technologies, assess their impact on existing processes and policies, and implement these technologies for the purpose of identifying criminal activity and preventing crime. Case studies from law enforcement organizations around the world will be examined to gain insights on their adoption approaches, challenges and results.

By the end of this training, participants will be able to:

• Combine Big Data technology with traditional data gathering processes to piece together a story during an investigation.
• Implement industrial big data storage and processing solutions for data analysis.
• Prepare a proposal for the adoption of the most adequate tools and processes for enabling a data-driven approach to criminal investigation.

Apache Druid is an open-source, column-oriented, distributed data store written in Java. It was designed to quickly ingest massive quantities of event data and execute low-latency OLAP queries on that data. Druid is commonly used in business intelligence applications to analyze high volumes of real-time and historical data. It is also well suited for powering fast, interactive, analytic dashboards for end-users. Druid is used by companies such as Alibaba, Airbnb, Cisco, eBay, Netflix, Paypal, and Yahoo.

In this instructor-led, live course we explore some of the limitations of data warehouse solutions and discuss how Druid can compliment those technologies to form a flexible and scalable streaming analytics stack. We walk through many examples, offering participants the chance to implement and test Druid-based solutions in a lab environment.

Format of the Course

• Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding

Learn how to Get & Transform Data to Prepare Interactive Dashboards

Power BI is one of the most popular Data Visualization tool, and a Business Intelligence Tool. Power BI is a collection of data connectors, apps, and software services, which are used to get data from different source, transforms data, and produce beautiful reports.

Power BI also allows you to publish them for your organization so that you can access them using mobiles, tablets etc. In this Power BI Tutorial, we will show you the step by step approach to connect with multiple data sources, data transformations, and creating reports like charts, tables, matrix, maps, etc

Pentaho Open Source BI Suite Community Edition (CE) is a business intelligence package that provides data integration, reporting, dashboards, and load capabilities.

In this instructor-led, live training, participants will learn how to maximize the features of Pentaho Open Source BI Suite Community Edition (CE).

By the end of this training, participants will be able to:

• Install and configure Pentaho Open Source BI Suite Community Edition (CE)
• Understand the fundamentals of Pentaho CE tools and their features
• Build reports using Pentaho CE
• Integrate third party data into Pentaho CE
• Work with big data and analytics in Pentaho CE

Audience

• Programmers
• BI Developers

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

• To request a customized training for this course, please contact us to arrange.

In this instructor-led, live training in Tunisia (onsite or remote), participants will learn how to use Microsoft Power BI to analyze and visualize data using a series of sample data sets.

By the end of this training, participants will be able to:

• Create visually compelling dashboards that provide valuable insights into data.
• Obtain and integrate data from multiple data sources.
• Build and share visualizations with team members.
• Adjust data with Power BI Desktop.

This instructor-led, live training in Tunisia (online or onsite) is aimed at data analysts and web developers who wish to develop associative models in Qlik Sense.

By the end of this training, participants will be able to:

• Apply Qlik Sense in data science.
• Use and navigate the Qlik Sense interface.
• Build a data literate workforce with AI interaction.
• Create a data-driven enterprise with Qlik Sense.

This instructor-led, live training in Tunisia (online or onsite) is aimed at engineers who wish to get data into Splunk Indexers and manipulate data in Splunk.

By the end of this training, participants will be able to:

• Use different data input methods and sources.
• Install, configure, manage and moniter Forwarders.
• Manipulate raw data in Splunk.
• Create a Splunk Diag.

The Only Course You Will Ever Need to Learn IBM SPSS Statistics, Research, & Data Analysis Scratch to Advanced Level

SSAS (SQL Server Analysis Services), is a Microsoft SQL Server transactional processing (OLAP) and data mining tool for analyzing data across multiple databases, tables or files. The semantic data models provided by SSAS are used by client applications such as Power BI, Excel, Reporting Services, and other data visualization tools.

In this instructor-led, live training (onsite or remote), participants will learn how to use SSAS to analyze large volumes of data in databases and data warehouses.

By the end of this training, participants will be able to:

• Install and configure SSAS
• Understand the relationship between SSAS, SSIS, and SSRS
• Apply multidimensional data modeling to extract business insights from data
• Design OLAP (Online Analytical Processing) cubes 
• Query and manipulate multidimensional data using the MDX (Multidimensional Expressions) query language
• Deploy real-world BI solutions using SSAS

Audience

• BI (Business Intelligence) professionals
• Data Analysts
• Database and data warehousing professionals

 
Format of the Course

• Interactive lecture and discussion
• Lots of exercises and practice
• Hands-on implementation in a live-lab environment

Course Customization Options

• This training is based on the latest version of Microsoft SQL Server and SSAS.
• To request a customized training for this course, please contact us to arrange.

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