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Pros & Cons of BigID: Analysis of a Leading Data Analytics Software

What are the pros and cons of BigID?
The pros and cons of BigID rest on its extensive capabilities in data discovery, data privacy management, data security, and data governance. Because it’s such a powerful data intelligence platform, it can be a bit complicated and intimidating to use. However, BigID has a technical support team ready to assist its customers.

Today’s world runs on big data. This data is so huge, fast, and complex that businesses need robust data analytics software to process and make sense of the data they collect. This is where BigID comes in. The data intelligence platform boasts features that make it easy for organizations to manage their data and meet ever-evolving security and data privacy regulations.

This article will discuss the pros and cons of BigID in detail. The pros of using BigID are plenty, including end-to-end automation, data discovery, and machine learning capabilities. But just like any platform or software product, there are cons as well.

bigid pros and cons

Big data can be a big headache for businesses. It’s humanly impossible and inefficient to use manual methods to identify, collect, and present data. It’s also a nightmare to keep up with different privacy regulations and suffer hefty fines for data misuse.
After data protection and privacy regulations such as the GDPR and CCPA took effect, organizations needed to double down on their strategies on proper data handling. Though these regulations do not provide a set definition of what is data privacy, they do lay out guidelines and best practices. The problem is these guidelines vary among the many different regulations. Manually checking and implementing compliance is just going to increase the risk of non-compliance and violations.

Moreover, cybersecurity is also a top concern for organizations when it comes to data protection. That is a very legitimate concern considering there was a 300% increase in reported cybercrimes since the onset of COVID-19. Hackers are more sophisticated and breaches are more common based on recent trends. Since GDPR, CCPA, HIPAA, and other data privacy legislation were implemented, companies have made data security a top priority. In fact, 66% said compliance mandates are driving their spending with 88% spending more than $1 million on GDPR compliance. However, only 59% of companies believed they were GDPR compliant and more alarmingly, 77% of organizations said they do not have an incident response plan in case of a breach.

What Are Companies Doing for GDPR Cybersecurity?

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Source: Varonis, 2021

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Overview of BigID

BigID dashboard

BigID is a leading data intelligence platform that enables organizations to manage all their data in one place. The platform includes a comprehensive list of modern features that cover data discovery, privacy management, security management, and data governance. It’s a solution to manage all types of data whether in motion or at rest, structured and unstructured, data in the cloud or your data center.

BigID is perfect for large organizations looking for a way to manage their critical data more efficiently. It leverages machine learning for compliance with a variety of data privacy and data security regulations. These include GDPR, LGPD, CCPA, NIST, and HIPAA. Businesses in healthcare, banking and finance, retail, and governments can highly benefit from using the platform.

Whether your organization wants cloud-based or on-premise data analytics software, BigID can be an excellent solution. BigID makes it easier for businesses to see an overview of their data and gain insights into the types of data they are collecting, processing, and sharing.

For data privacy management, BigID uses data-driven privacy compliance and automation. Some of the important tools included are those for consent governance, PIA automation, and RoPA data mapping. With its powerful AI and ML capabilities, BigID takes away the fear from many companies when it comes to complying with ever-evolving data privacy and protection across all their data stores.

Detailed BigID Review

The following are key features of BigID:

  • Data Discovery
  • Privacy Management
  • PI Inventory
  • Risk Management
  • Sensitive Data Identification
  • Breach Data Investigation
  • RoPA mapping
  • Consent management
  • ML-Augmented Data Catalog
  • Access Controls/Permissions

BigID Pros and Cons

Data Privacy Automation

Keeping up with new and emerging data privacy and protection regulations is a complex undertaking. With the large volume of data produced every day, how do companies effectively find, map, classify, and inventory the sensitive data they have? The answer lies in data privacy automation. BigID comes with an extensive privacy management suite that makes it easy for organizations to remain on top of data privacy compliance.

For example, privacy preference management enables businesses to quickly respond to and manage data rights requests. These include cookies and consent opt-in or opt-out. Companies can also perform data lifecycle management where they manage structured and unstructured data and implement data retention and deletion policies based on regulations.

Moreover, BigID has DSAR automation capabilities that allow organizations to automate end-to-end data rights fulfillment and reporting. One of the benefits of DSAR automation is that you can quickly locate all the data kept on an individual across all data sources. BigID identifies personal and sensitive data, including PII, PI, NPI, and SPI, and automatically determines to whom it belongs.

BigID consent preference

Quickly respond to and manage data rights requests, cookies, consent opt-in, opt-out.

ML-driven Data Classification

Traditional pattern-based classification is no longer enough to properly handle today’s big data analytics. BigID leverages artificial intelligence, machine learning, and deep learning applications to classify all types of data—unstructured or structured, documents, images, mail, and data-at-rest, and data-in-motion. These advanced features together with the platform’s patented file analysis classification all work together to add context to independent data points and correlate them to individual identities. As a result, organizations can create their personal data catalog and get full visibility over the personal, consumer, and entity data they collect, store, and share.

Unsupervised machine learning is also used in BigID’s cluster analysis. Organizations can automatically identify similar, redundant, and duplicate data across their entire data landscape with fuzzy classification. Fuzzy classification allows you to quickly filter data by sensitivity, attributes, data sources, and duplicates. Also, ML capabilities make it possible to quickly identify similar content within files and accelerate data visibility wherever the data lives—in the cloud, on-premise, or a hybrid of both.

AI, ML, and deep learning are also powering BigID’s advanced data classification for sensitive data. This makes compliance less troublesome and complicated for businesses as the platform can automatically search for, identify, and classify regulated data like PCI and HIPAA. It also classifies personal data like PII and contextual PI, NPI data, credentials, passwords, and security keys, IP data, and document types.

The features highlighted so far are just a few of the capabilities of BigID. For something as complex as big data analytics, you can imagine how no platform can ever be a simple plug-and-play one. Expect some challenges when trying to learn all the tools and features of BigID. The user interface is clean but you’ll still need to spend some time trying to find where specific tools are and how to get the more complex functions to work.

BigID cluster analysis

Fuzzy classification helps identify similar, duplicate, and redundant data for a layered classification and discovery approach.

Data Security Capabilities

Privacy regulations such as GDPR and CCPA require organizations to not only identify data related to an individual but also be responsible for protecting that data. Protection entails monitoring and reporting who the data belongs to, where it came from, and where the data’s going. BigID helps organizations succeed in data protection and remediation with discovery in-depth.

Discovery in-depth consists of the 4 Cs: catalog, classification, cluster analysis, and correlation. These methods of data analysis and discovery work together in a privacy-centric approach to provide unmatched protection of personal and sensitive data across all company sources. Using the discovery in-depth approach means organizations have a 360° visibility over the types of data they collect and what sensitive data need to be protected.

Aside from leveraging machine learning-driven data discovery to classify all data, BigID also performs data risk scoring. The platform automatically measures risk based on parameters such as location, data type, and residency. You can further customize these parameters across data, assets, and elements to suit the requirements of your industry and proactively protect data.

File access intelligence, on the other hand, delivers next-generation file access management. It identifies and remediates overexposed data and over-privileged users or groups. As a result, your team can quickly flag high-risk, sensitive, and regulated data. They can review file clusters containing sensitive data and limit or control access to it. It’s also possible to create audit reports of high-risk targets so you can make the necessary changes in permissions and reduce risk.

BigID file access intelligence

Identify high-risk data and over-privileged users. Quickly flag high-risk, sensitive, and regulated data.

Efficient and Scalable Data Governance

A well-designed data governance program mitigates risk and gives organizations a competitive advantage by building trust among their customers and stakeholders. With BigID’s governance suite, organizations can perform consistent, efficient, and scalable data governance. ML-prompted validation, for example, replaces traditional manual curation for faster, more accurate, and unified data management and cataloging.

Moreover, it becomes easier to monitor data quality, consistency, and completeness since users have a unified view of all data across their organization’s entire ecosystem in a single data catalog. You can define data quality rules either by column or attribute then evaluate results to check for inconsistencies and overall data quality across data sources.

BigID data catalog

Discover all data across your entire ecosystem in a single data catalog.

Privacy, Protection, and Perspective Using BigID

Big data will usher businesses to new growth but it also comes with tough challenges. In today’s digital world governed by data rights and privacy regulations, data has become a top risk for organizations. Therefore, using an ML-driven data intelligence platform has also become a necessity. This guide on the pros and cons of BigID should point you in the right direction.

The platform’s capabilities when it comes to data discovery, security, privacy, and governance are reliable and comprehensive. It’s built for enterprise use and includes cutting-edge technology and tools like automation and deep learning. Plus, BigID is a scalable solution that can help businesses efficiently manage enterprise data volume and data sources with minimal disruption to their systems and workflows.

The challenge when using BigID is finding your way around the user interface. Customizing settings and parameters for automated risk management, for instance, will probably demand technical skills and background. In other words, there can be a steep learning curve when trying to figure out the platform. When you do hit a wall along the process, you can always tap BigID’s expert technical support team for assistance.

Nestor Gilbert

By Nestor Gilbert

Nestor Gilbert is a senior B2B and SaaS analyst and a core contributor at FinancesOnline for over 5 years. With his experience in software development and extensive knowledge of SaaS management, he writes mostly about emerging B2B technologies and their impact on the current business landscape. However, he also provides in-depth reviews on a wide range of software solutions to help businesses find suitable options for them. Through his work, he aims to help companies develop a more tech-forward approach to their operations and overcome their SaaS-related challenges.

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