Understand the full scope of data applications in business
Limiting the field of data application from the start will hinder creativity and vision of students as they engage on projects. By understanding the spectrum of possibilities, students will grow bolder in the analytics they undertake.
Architect systems for agility and scalability in a true partnership with IT
By avoiding initial critical errors, students can design ultra-lean and efficient frameworks that they will not only tailor to their needs but also control. Understand what should drive the implementation of systems to best position them in your organization:
- Learn the core system components of the analytics stack to best leverage and connect them
- Become comfortable with technology to engage with confidence and impact with IT and your vendors
- Smart select your vendors and engage them with best synergies
Lead rapid implementations that deliver quick wins and sustainability
From setting the right vision, to defining the project pace, selecting the technology and the consultants, many things will go in the way of a successful plan. Learn how to limit risks by avoiding classic mistakes and knowing when to take the right calls.
Harness data with ease and transparency
Data is business raw material and pre-analytics processing is almost as important as the final analysis. Understanding and recognizing data types enables the design of elegant and efficient models and preparation processes that will lead to faster insight with minimal error risk.
- Seize the breadth and depth of the data universe
- Understand databases and how different technologies apply to different business needs
- Learn the data families (Facts, Master Data, Meta Data, Calculated Data) to optimize their leverage for fast and flawless analytics
- Understand what are the paradigm changes with Big Data
Lead Data Quality and Master Data Management for best analytics results
A large and often hidden part of data management relies on quality control and alignment work. Mastering the base of these techniques is key to make progress without being hindered with bad data.
Becoming an advocate of a data culture and a change leader
The most common weakness in data project will be the human factor. Identifying the internal and external dynamics of projects and knowing their potential impacts will help leaders to proactively manage transition and foster engagement
- Understand the required managerial changes that must happen with data projects
- Identify and mitigate resistance to change
- Leading with curiosity and design thinking mindset
Design processes for performance and sustainability
System, data and people must be organized around processes that achieve the subtle balance between what technology can deliver, the state of the data sources (quality, completeness) and the readiness of the team. If best practices are always a good base from which to start, a focus on speed and repeatability will free up time to create additional business value.
- What makes processes sustainable?
- Identify the key components of any data process
- Learn how to position systems optimally
The next frontier in data for business
Big Data technologies are bringing in many options for the business. By remaining focused on addressing business challenges will help students finding their way in the vast array of new solutions. As volume and analytics capabilities are exploding, the foundation of data projects still hold and become even more important to avoid the “Bigger” pitfalls of Big Data:
- Understand where technology and approaches are shifting?
- What new approaches really makes sense for business?
- How should you balance the “walk before fly” with data?
- What are the true impacts of engaging in Big Data? How can you get ready for them?
Module 6 – Only available for 2 and 3-day trainings
Build a complete project, straight from the best practices learned in the class and solidify new understanding with an applied case study.
- Create and automate data capture
- Design data quality checks
- Optimize your data for business analytics
- Run analysis and automate reporting
- Connect external data to enrich your view
A Customizable Base
The training covers the 4 facets of digitalization (technology, data, people and processes) which are presented over a 1 to 2-hour session or 1, 2 or 3-day training. Each format covers the same breadth topics, ut offers different level of depth in the content adjusted to meet customer focus.
The 2 and 3 day classes can also include 1 hands-on case study that covers analytics from raw data to dashboard
They can be completed by an optional data hacking and advanced visualization workshop and a graded test.
Pricing is set per participant following the table below.
1/2 Day Session
- Plus $180/participant (25-50 participants)
- Plus $120/participant (50 or more participants)
1 Day Session
Plus $220/participant (25-50 participants)
Plus $180/participant (50 or more participants)
2 Day Session
Plus $320/participant (25-50 participants)
Plus $280/participant (50 or more participants)
3 Day Session
- Plus $500/participant (25-50 participants)
- Plus $460/participant (50 or more participants)