The Information Governance (IG) concept has been around for years. Implementation has proven difficult to downright impossible because the domain is so broad. Enterprise-wide IG is massively scaled, crossing workgroups, location, data types, and business process boundaries. When the enterprise determines to implement IG, it faces the prospect of developing new processes and technology across the entire organization. In addition, the enterprise faces dynamic changes over time: as information management needs morph and shift over the years, IG morphs right alongside them.
Given this broad scale, organizations have the best chance for success by concentrating on the highest risk and biggest pain points that can benefit from IG. IT’s domain has a big claim, particularly with unstructured data. Unstructured data rates are hitting 75-80% of corporate data, and data growth is increasing 35-50% year-over-year. In the midst of this massive data growth, IT is directly responsible for data lifecycle management, user access, data security, and compliance. They are also frequently involved with eDiscovery collections and big data analysis.
These represent big challenges – and IG tools concentrating on unstructured data directly benefit all of these processes. Introducing IG into the data management domain is best done with a combination of technology toolsets and organization priorities that drive policy settings. This combination can deliver IG to manage data across the data center and the organization. And often the same tools can extend to additional workgroups including Legal, Records Management and Business Analysis.
What Information Governance can do for IT
One of IT’s biggest responsibilities is to manage unstructured data. Data of this type exists in many different formats and locations, which makes it a challenge (to say the least) to manage. Governing this data takes IG technology that can intelligently manage many different types of data for compliance, lifecycle, and value.
File analysis platforms are IT’s primary means to deliver IG services to unstructured data. Modern file analysis offers more than basic metadata mapping and alerts: they classify on a rich variety of characteristics and do so at massive scale. They also offer sophisticated query and policy support.
File management products range from specialized storage systems to software that universalizes classification and policies across multiple data sources. The latter has the advantage in governing data across the enterprise. This enables IT to manage files across different storage systems, application servers, and the cloud. This is a big benefit: the cloud environment is subject to the same data management issues that affect files stored behind the firewall. It gets even more complicated because “the cloud” is not a monolithic location. Organizations and employees may be storing files in Office365, public cloud providers, Box or Dropbox, and more. Distributed IG toolsets can discover and analyze files in the cloud as well as on-premise.
Acaveo Smart Information Server (SIS) is an example of distributed file analysis. Acaveo centralizes operational intelligence for files located across multiple on-premise, distributed and cloud data sources. The platform discovers files, classifies them by many characteristics, and applies policies. Irish company Ostia developed Portus to map system and application dependencies between different IT systems.
Storage makers also provide IG tools for unstructured data. Tarmin’s GridBank software uses a global namespace to pool data across distributed storage hardware. GridBank aggregates storage and IG services including data management, search, eDiscovery and analytics. Newcomer Qumulo offers massively scaled storage systems with intelligent data analysis tools. Built-in intelligence discovers, retrieves, and manages massively scaled data located in its system.
Storage system vendors also engineer IG services into their arrays. IBM and HP offer IG services around big data. EMC’s SourceOne division houses its formal IG offerings. SourceOne eDiscovery tools include collection and early analysis, and SourceOne File Intelligence offers file-based information governance.
IT is also responsible for security and compliance, unstructured big data, and often eDiscovery collections and early analysis.
IT employs user access control to secure data. Sadly, many IT departments lack strong compliant policies for user and role access settings. IG tools can strengthen access control by discovering file and folder access settings, and remediating security holes. IT is also responsible for securing sensitive data containing personally identifiable, credit or health information. IG tools can discover and identify this sensitive data, allowing IT to move or delete information as needed. Vendors like Acaveo that offer strong integration with Active Directory can close big access security holes.
Big data analysis frequently uses unstructured data as its information source. The issue is that this same data is spread around multiple applications and locations, and may or may not be easily accessible for meaningful analysis. IG tools can identify big data sources by set characteristics and apply trend analysis across a wide universe of data.
Unsurprisingly, IBM is a major player in governing big data. IBM InfoSphere operates across unstructured and unstructured data, with deep integration between data sources and standardized processes for big data management and reporting. IBM also owns eDiscovery platform StoredIQ, which includes data analysis and governance in its software suite. HP offers a full complement of information governance tools for big data under its Intelligent Retention and Content Management platform. The suite integrates HP StoreAll, ControlPoint and Records Manager to govern data residing on HP Haven big data storage.
eDiscovery is a perennial IG development driver, with software tools existing to aid in collection and analysis throughout the EDRM workflow. In addition, eDiscovery software makers often engineer their products to work with related processes including records management and compliance. IG-related eDiscovery tools are not relegated to eDiscovery software makers: file analysis products often provide eDiscovery tools as well.
Of the pure eDiscovery vendors, Exterro is a full-service eDiscovery provider whose platform includes IG tools like E-Discovery Data Mapping. AccessData and Nuix Luminate also provide robust IG tools.
Conclusion
IT is more used to thinking in terms of managing data then governing it. Data management seems practical and achievable, while governance seems to be an exercise in controlling the uncontrollable. It doesn’t help that IG relates to multiple workgroups and processes throughout the enterprise. However, IG technology can directly benefit data management – and governance, and compliance, and security. These are all domains critical to IT. In this age of massive unstructured data growth, managing data for compliance and value is a top priority for IT. The IG tools to manage it are available today.
Photo courtesy of Shutterstock.
Huawei’s AI Update: Things Are Moving Faster Than We Think
FEATURE | By Rob Enderle,
December 04, 2020
Keeping Machine Learning Algorithms Honest in the ‘Ethics-First’ Era
ARTIFICIAL INTELLIGENCE | By Guest Author,
November 18, 2020
Key Trends in Chatbots and RPA
FEATURE | By Guest Author,
November 10, 2020
FEATURE | By Samuel Greengard,
November 05, 2020
ARTIFICIAL INTELLIGENCE | By Guest Author,
November 02, 2020
How Intel’s Work With Autonomous Cars Could Redefine General Purpose AI
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
October 29, 2020
Dell Technologies World: Weaving Together Human And Machine Interaction For AI And Robotics
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
October 23, 2020
The Super Moderator, or How IBM Project Debater Could Save Social Media
FEATURE | By Rob Enderle,
October 16, 2020
FEATURE | By Cynthia Harvey,
October 07, 2020
ARTIFICIAL INTELLIGENCE | By Guest Author,
October 05, 2020
CIOs Discuss the Promise of AI and Data Science
FEATURE | By Guest Author,
September 25, 2020
Microsoft Is Building An AI Product That Could Predict The Future
FEATURE | By Rob Enderle,
September 25, 2020
Top 10 Machine Learning Companies 2020
FEATURE | By Cynthia Harvey,
September 22, 2020
NVIDIA and ARM: Massively Changing The AI Landscape
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
September 18, 2020
Continuous Intelligence: Expert Discussion [Video and Podcast]
ARTIFICIAL INTELLIGENCE | By James Maguire,
September 14, 2020
Artificial Intelligence: Governance and Ethics [Video]
ARTIFICIAL INTELLIGENCE | By James Maguire,
September 13, 2020
IBM Watson At The US Open: Showcasing The Power Of A Mature Enterprise-Class AI
FEATURE | By Rob Enderle,
September 11, 2020
Artificial Intelligence: Perception vs. Reality
FEATURE | By James Maguire,
September 09, 2020
Anticipating The Coming Wave Of AI Enhanced PCs
FEATURE | By Rob Enderle,
September 05, 2020
The Critical Nature Of IBM’s NLP (Natural Language Processing) Effort
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
August 14, 2020
Datamation is the leading industry resource for B2B data professionals and technology buyers. Datamation's focus is on providing insight into the latest trends and innovation in AI, data security, big data, and more, along with in-depth product recommendations and comparisons. More than 1.7M users gain insight and guidance from Datamation every year.
Advertise with TechnologyAdvice on Datamation and our other data and technology-focused platforms.
Advertise with Us
Property of TechnologyAdvice.
© 2025 TechnologyAdvice. All Rights Reserved
Advertiser Disclosure: Some of the products that appear on this
site are from companies from which TechnologyAdvice receives
compensation. This compensation may impact how and where products
appear on this site including, for example, the order in which
they appear. TechnologyAdvice does not include all companies
or all types of products available in the marketplace.