Tag: Machine Learning

How to Prioritize Risk Across the Cyberattack Surface

Research Desk

Security leaders need to understand vulnerabilities in context and use that data to prioritize their team’s efforts. But, there’s a problem: The number of vulnerabilities has nearly tripled in the last couple of years, creating too much data for teams to process on their own.
Download this whitepaper to learn:

  •  Why CVSS is a poor indicator of risk and fails as a tool for prioritization
  • How machine learning capabilities can help you predict the vulnerabilities most likely to be exploited
  • Why it’s essential to factor in asset criticality when prioritizing vulnerabilities for remediation
    Download How to Prioritize Risk Across the Cyberattack Surface now.

How to Implement Risk-based Vulnerability Management

Research Desk

Don’t rely only on CVSS to prioritize. Use machine learning to predict what is most likely to be exploited.

BODY: Risk-based vulnerability management helps you prioritize your remediation efforts to focus on the vulnerabilities and assets that matter most. Risk-based VM can help you make the most efficient use of your limited security resources by making the biggest impact on risk with the least amount of effort. Ready to make the move to risk-based VM? Download the eBook: https://www.tenable.com/whitepapers/how-to-evolve-to-risk-based-vulnerability-management

Customer Data Platforms 101: Everything You Need To Know

Research Desk

What CDPs are and the capabilities they should offer

Marketing is all about data. But pulling together customer data from all relevant sources, creating unified, regularly updated customer profiles and then using this customer data to achieve a range of business goals is challenging.

Customer data platforms (CDPs) are solutions that allow you to collect data, unify customer profiles, understand your customer segments and put your data to work. While organizations often rely on other solutions to manage their customer data – CRMs, DMPs, MSPs and data lakes – CDPs offer far more functionality and tangible benefits than these solutions.

When selecting a CDP, organizations have to pay special attention to the capabilities it offers. Specifically, organizations will get more out of their CDP when it unifies ALL available customer data, when it offers machine learning and data modeling features that make customer data actionable, when it provides meaningful reporting and when it ensures consistent data quality.

Plan to Win – Achieving business agility in the age of urgency

Research Desk

By: Adaptive Insights (A Workday Company)

Type: eBook

Plan to Win reflects the collected experience and wisdom gained from working with thousands of companies, the insights of CFOs and FP&A practitioners, and other thought leaders, as well as research on how planning impacts business performance. The book sets forth a clear vision for where strategic business planning is headed and the impact it can have on your organization.

Use this eBook as a guide to embrace a new model of business agility, in which planning and execution converge into an entirely new discipline—an ongoing, closed feedback loop of planning, execution, measurement, and adjustment.
Chapter highlights:
Chapter 3: Active planning: a new model for business agility
Chapter 4: The central role of finance in business agility
Chapter 5: Driving better planning throughout the organization
Chapter 9: Agility, AI, and machine learning – preparing to capitalize on the future

Sponsor  By: Workday

Six Things You Need to Know about Machine Learning to Be Successful

Research Desk

Today, the vast majority of organizations realize they need to digitally transform to compete. Many organizations want to accelerate this change, and data science tools such as machine learning are at the heart of this.

This checklist report by TDWI (Transforming Data with Intelligence) and sponsored by Snowflake focuses on six technology considerations for successful machine learning and data science.

The checklist will cover:

  • How organizations that utilize advanced techniques like machine learning are more likely to see an impact on their bottom line
  • Why you should consider a cloud data platform for data management
  • Tips to collecting and understanding the useful data needed to train a machine learning model
  • The importance of feature engineering
  • Key elements to deploying a machine learning model within your company