Five Best Practices for Data Security in Modern Cloud Platforms

Released: Aug 29, 2023 |

Length: 9 pages |

Language: English |

Resource: Whitepaper

Data is becoming increasingly complex as organizations build out their analytics capabilities and become more competitive. TDWI research indicates that organizations are increasingly collecting not only structured data but unstructured and semistructured data as well. They are also gathering machine-generated data and streaming data types and are interested in utilizing and combining data from their SaaS applications and third-party cloud providers to enrich their data sets for analytics

Work email *

First Name *

Last Name *

Job Title *

Company Name *

Phone *

Address Line 1 *

City *

Zip/Postcode *

Country *

Industry *

Company Size *

What Data Security Platform challenges are you struggling with? *

Protecting multi-cloud environments

Meeting data privacy and compliance regulations

Security policy orchestration

Reducing the number of policies needed to manage data

Enabling zero trust

Understanding how sensitive data is being used and by whom

Addressing new data security requirements quickly

Preventing data leakage

Enforcing data control and access policies

Securing data access across the data mesh

Implementing a secure data exchange platform

Analyzing compliance risk

Cloud data migration

Securing a hybrid and remote workforce

None of the above

What do you hope to achieve when the Data Security Platform solution is in place? *

Automate data discovery and classification

Simplify policy creation and management for non-technical stakeholders

Identify anomalies in data access before they can become larger issues

Real-time, prioritized view of data security and compliance posture

Continuously remediate data exposure and misconfigurations

Improve collaboration across security, platform, and governance teams

Streamline data sharing across lines of business, geographies, and third parties

Automatically discover, classify, and label sensitive data

Build location-based data policies

Continuous data usage monitoring

Dynamic data masking

Protect data without having to write code or copy data

Unified view and enhanced insights to at-risk data and users

None of the above

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