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Introduction

Identity management increasingly incorporates analysis capabilities, and good analysis depends on well-managed data. The managed data lake methodology provides a holistic approach to identity management by providing a single source of truth for data.

Highlights

  • Modern identity management is highly diverse and distributed, spanning multiple systems, platforms, and devices.
  • Proper governance of data enables more data to be used in analytics, while also protecting privacy for sensitive classes of data.
  • With the role of analytics in identity management increasing, the managed data lake model provides a single source of truth for data.

Features and Benefits

  • Identifies the current changes in the identity management market, including the growth in data relating to customer and citizen identities.
  • Assesses the factors contributing to the increasing scale and complexity of identity management.
  • Examines the growing role of analytics in modern identity management, and the information management challenges that accompany it.
  • Identifies the problems with the "stop and block" mentality toward data security and protection.
  • Evaluates how the managed data lake can help complement identity management efforts.

Key questions answered

  • How has identity management changed to incorporate the growth in consumer identities and devices?
  • What data management challenges exist due to the increased scale and scope of data involved in modern identity management?
  • How does the managed data lake support the growing use of analytics in identity management technology?
  • Why is inheritance of policy controls important for systems sitting on top of the managed data lake?
  • How can the managed data lake increase security and privacy while liberating more data for analysis?

Table of contents

Summary

  • Catalyst
  • Ovum view
  • Key messages

Recommendations

  • Recommendations for enterprises
  • Recommendations for vendors

Modern identity management is highly distributed

  • Identity management is increasingly externally focused
  • The proliferation of devices and applications obfuscates identity

Governance acts as an enabler of data resources

  • Identity management solutions increasingly incorporate analytics
  • Governance is needed to change the "stop and block" mentality

The data lake complements identity management

  • For analytics results, data is best controlled at the base layer
  • For data to be controlled at the base layer, a data lake is helpful

Appendix

  • Methodology
  • Further reading
  • Author

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