- Charles Tatosi Chavapi – Information Security Manager, Debswana Mining Industry
- Ken Dewitt – IT Director, Navajo County
- Jim Finlayson – IT Director, City of Grand Junction
- Lian Guan – Enterprise Information Management Advisor, Ontario Lottery and Gaming Corporation
- Diane Kelly – Information Security Manager, Colorado Judicial ITS
- Leon Letto – Senior Technical Sales Engineer, AirWatch
- Jim McGann – VP, Marketing and Business Development, Index Engines, Inc.
- William Mendez – Information System Security Officer, City of Miami
- Ian Parker – Head of Corporate System Information Security, Risk, and Compliance, Fujitsu Services
- Claudiu Popa – President & CEO, Informatica Corporation
- Doug Waram – Director of IT, County of Wellington
- Chris Whiting – Solutions Architect, APA Group
- 3 anonymous contributors
- Huge volumes of data, in all different types, make data discovery a daunting task. With such backlogs of information, it can be difficult figuring out where to start classification.
- Ad hoc classification systems may lack consistency and accountability. Which formal classification system is right for you?
- End users are one of the weakest links in data security. Relying on end users to accurately classify and handle sensitive information requires significant awareness and training.
- Avoid analysis paralysis. Classifying all your data at once may not be feasible. Start small, quantify your results, report it to management, and then go back and tackle a larger portion.
- Data is dynamic. Data, by its nature, does not stay static. A piece of data’s criticality will peak, but strategic reassessment will eliminate over/under protection of data. Data classification must be a program, not a project.
- Classify what matters. Focus the program on data whose classification is measurable, auditable, and manageable.
Impact and Result
- Formalize the data classification initiative with the proper policies and handling standards, as well as a structured steering committee to ensure accountability and consistency.
- Understand where your data lives and what controls are implemented to protect the data. Make sure the protection is proportional to the sensitivity and criticality of the assets.
- Understand what tools are available to implement an efficient data classification program – whether provided from a third party or done in-house. Know how and when to revisit classifications to keep them up to date.
Start here – read the Executive Brief
Read our concise Executive Brief to find out why you should define and develop a data classification program, review Info-Tech’s methodology, and understand the four ways we can support you in completing this project.
1. Define the requirements
Formalize your data classification steering committee, classification scheme, and documentation.
2. Discover the data
Perform data discovery to understand where your most sensitive data resides.
3. Implement data classification
Perform data classification and draw out valuable insights to drive strategic security decisions.
This guided implementation is a six call advisory process.
Guided Implementation #1 - Define the requirements
Call #1 - Formalize the Data Classification Steering Committee
Formalize data classification documentation
Guided Implementation #2 - Discover the data
Call #1 - Plan for data discovery
Call #2 - Ease the task of classification
Guided Implementation #3 - Implement data classification
Call #1 - Fill in the Data Classification Inventory Tool
Call #2 - Analyze results
Call #3 - Maintain and optimize the program
Book Your Workshop
Onsite workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn't enough, we offer low-cost onsite delivery of our project workshops. We take you through every phase of your project and ensure that you have a roadmap in place to complete your project successfully.
Module 1: Define the Requirements
- Define and formalize the data classification program to fit your organization’s needs.
Key Benefits Achieved
- A right-sized classification program with formal documentation laying the foundation
Assemble the Data Classification Steering Committee
- Established Data Classification Steering Committee Members
Define the Data Classification Steering Committee Charter
- Formalized Data Classification Steering Committee Charter
Determine the classification scheme
- Defined data classification scheme
Develop the Data Classification Policy
- Formalized Data Classification Policy
Develop the Data Classification Standard
- Formalized Data Classification Standard
Module 2: Discover the Data
- To effectively mitigate risk and classify data, you must know where your data resides.
Key Benefits Achieved
- Initial insight into where your data resides
Develop questionnaire to conduct data discovery with key data owners
- Questionnaire to conduct discovery interviews
Interview key departments / data owners
- Preliminary data discovery interview results
Identify where to prioritize classification
- Prioritization of assets to classify
Re-evaluate policy and standard
- Finalized policy and standard documents
Module 3: Implement Data Classification
- Classify the data to inform strategic security decisions.
Key Benefits Achieved
- Development of supporting evidence regarding current state of data protection based on classification to drive future security initiatives
Classify data in the inventory tool
- Data classification inventory starting point
Analyze results of the preliminary classification
- Security and location analysis charts to share with management
Begin developing a data classification training and awareness program
- Plans for training and awareness
Determine metrics to measure the effectiveness of the program
- List of metrics