Users: Head of Records Management group, IT administrator, governance user.

A Day in the Life (Before):

Scene or Situation: Sharon V. is the Head of Record Management within a major enterprise institution who has just been told by federal regulators that there is concern of the risk created with the large disorganized collection of their dark unstructured content. If it is not organized and cleaned up, the enterprise will face penalties and a possible downgrade in rating. Sharon has brought Ron, the Governance user, and Kapil, their IT administrator together to find the solution.

Desired outcome: Find solutions that identify and preserve business relevant information and destroy what is not relevant.

Attempted Approach: Ron and Kapil have been investigating ways to solve this problem by identifying all of the different data types they need a solution for. So far, they have been looking at email archiving, deduping, governance, immutability, and defensible destruction software.

Interfering factors: Ron and Kapil have presented Sharon with several solutions that would provide incremental value toward their objective, but not entirely solve their problem. Each of these solutions will require individual implementations. Each implementation will require significant resources to accomplish and cannot all be done at once. Sharon is concerned it will not be done before their next audit by regulators.

Economic Consequences: While Ron and Kapil have worked hard to present a number of solutions, Sharon is not happy with the time it will take to implement all of these solutions. Nor is she happy that her problem will only be partially solved by these disparate solutions. Not only are they all very costly, but if not completed in time federal regulators will impose stiff penalties on the company. The penalties will be severe enough to damage the reputation and stability of the company.

A Day in the Life (After):

New Approach: Ron and Kapil have found a number of different solutions that promise collectively to solve the problem Sharon has asked them to solve. However, the idea of burdening their already taxed IT department with these multiple implementations leaves them feeling uneasy and has increased their tasks, not lessened them. By branching their options to an agile technology company they have discovered a single solution that will be able to ingest information from all of their multiple sources. With this solution, they will finally be able to better govern their information as it is now centrally accessible in one interface.

Enabling Features: With the Infobelt Governance Platform [IGP] Ron and Kapil were able to leverage the inspection tool to provide rich visualization and metadata on their information sources. They now know the contents, file types, sizes, etc. of this previously dark data. Upon ingestion and content indexing of this information, IGP provides Ron and Kapil with auto-clasification logic, helping them quickly make decisions about which information is relevant and still retains business value and which information should be destroyed. Now Ron and Kapil understand what information they have, where it is, what needs to be preserved, and what needs to be destroyed. They are also able to wrap these unique data sets with the appropriate compliance and governance rules to protect its integrity.

Economic Rewards: Sharon is thrilled with a single solution provider. She knows she is going to save time in implementation, and as a result save significant cost in the process. It will also save her from the pending regulatory fines, and reputational damage. Not only has her acute problem been solved but they have now implemented a solution that will continue to reduce their information risk over time by allowing Ron to easily apply and monitor governance and regulatory information practices.

  • Fast and simple installation
  • Hosted internally
  • Database agnostic
  • Intuitive UI
  • Quick setup
  • No capital investment needed
  • Off-premise/hybrid
  • On-premise
  • Lower cost of entry
  • Software and hardware configurations
  • Appliance model in 50, 150, and 300 terabytes
  • Scalable with modular storage units

Our platform engages users in multiple organizational disciplines from records managers to legal counsel to IT teams. To provide the best experience for each user, we offer an intuitive GUI interface with simple and powerful wizard functions.

For those users who need a more technical ‘under the hood’ interaction with IGP, our API allows the user to create their own scripting interface. This feature allows companies who have dynamic integration constraints to customize IGP for their unique workflow and process requirements.

Preview allows the user to view the total size of content on an Information Store and the total size of the files prior to archiving.

During the archive process IGP pulls content from Information Store and makes those items into immutable artifacts. The artifacts are archived to the selected configured Archive Store according to a user-created channel. IGP does not move the original files from the Information Store, but rather creates a copy that is archived. It is on the roadmap for IGP to eventually have the ability to delete the original files from the Information Store.

IGP allows the user to run a Verify task to reconcile that archived content is consistent between the OMR and the Archive Store. The Verify task can optionally also check against an Information Store to alert the User its state has been altered (i.e. files have been deleted, added, or changed in the Information Store). Additionally, the user can verify an Extract task to ensure that the extracted set of files matches the Archive Store from which they were pulled.

This task indexes the physical metadata associated with each artifact as well as the full text in those artifacts. This enables the user to search based on metadata and/or content within the files themselves. It is on the roadmap for IGP to have the ability to index images and other media formats in addition to the current text indexing.

After ingesting content into IGP, the user can opt to compress the artifacts with this task. The Compress task does not affect container formats (.zip, .tar, etc.) or media files.

IGP allows the user to search indexed content via the web user interface. The search feature allows the user to search on physical metadata or based on the text content of archived, indexed data.

Artifacts are extracted as uncompressed files from the Archive Store to a local staging area to allow the user to perform eDiscovery or examine the content of files.

IGP performs defensible destruction based on governance policies assigned by the user. The user must schedule a recurring Destroy task that will then automatically destroy artifacts that have reached their retention periods according to the user defined frequency. Post destruction, the user can view a destruction list that shows which objects have been destroyed.

Gartner defines information governance as the specification of decision rights and an accountability framework to ensure appropriate behavior in the valuation, creation, storage, use, archiving and deletion of information. It includes the processes, roles and policies, standards and metrics that ensure the effect and efficient use of information in enabling an organization to achieve its goals.

Archived content cannot be altered once it has been ingested. IGP does not allow users to modify files in the Archive Store in any way. Files that are Extracted from IGP and altered are viewed as new objects by the system and Archived.

IGP allows the user to place archived content on legal hold so that it will not be disposed of even when its retention period expiration is reached. If the legal hold is lifted the files will be eligible for destruction based on its retention period disposition date.

IGP allows the user to run a Verify task to reconcile that archived content is consistent between the OMR and the Archive Store. The Verify task can optionally also check against an Information Store to alert the user its state has been altered (i.e. files have been deleted, added, or changed in the Information Store). Additionally, the user can Verify and Extract task to ensure that the extracted set of files matches the Archive Store from which they were pulled.

The system allows the user to leave a “stub” in place of a file after it has been Archived into IGP and deleted from the Information Store. The stub will contain basic file metadata.

IGP’s Preview task allows the user to view the total size of an Information Store and the total size of the giles prior to archiving. In the future this will be an advanced module that allows the user to explore content on the Information Store prior to archiving and discern the types of files that exist as well as other analysis.

During the Archive process IGP pulls content from Information Stores and makes those items into immutable artifacts. The artifacts are archived to the selected configured Archive Store according to a user-created channel. IGP does not move the original files from the Information Store, but rather creates a copy that is archived. It is on the roadmap for IGP to eventually have the ability to delete the original files from the Information Store. Once the content has been successfully Archived, IGP automatically runs a Verify task to ensure that the archived content and the OMR are in sync.

In the event of an operational failure, IGP offers reliable rollback capabilities to ensure that the database and Archive Stores are restored to a consistent state.

IGP maintains a record of system events and updates. When any of the system tasks are performed (Preview, Archive, Verify, Index, Search, Compress, Extract, Destroy) the activity is logged and a record is kept of the associated date and timestamp as well as any user connected to that action.

Underlying Technology Architecture

There are three main elements of our underlying technology architecture.

  1. First, at its core, our platform is written in Java, the enterprise standard for large scale application development. With its vast array of libraries it is able to help overcome the challenges that often occur when developing enterprise applications.
  2. Second, the Infobelt Governance Platform utilizes a REST application program interface (API) as the foundation for its simple and scalable data archiving and governance solution. This allows the platform to have tremendous flexibility and interoperability with other products. For example, the use of a RESTful architecture allows Infobelt to create APIs to interface with other storage applications including CAS and NAS, or cloud services like Amazon.
  3. Third, our platform is purpose built to be database agnostic. Not only does this make our platform flexible to meet the needs of today’s enterprise, but it also provides the kind of adaptability required to meet an ever-changing technology landscape. By supporting all JDBC compliant databases, our platform does not limit your ability to make the best technology decision for the enterprise.

Unstructured data is all the content that can’t be so readily classified and fit into a neat box: photos and graphic images, videos, streaming instrument data, webpage, pdf files, PowerPoint presentations, emails, blog entries, wikis and word processing documents. Techniques such as data mining provide different methods to find patterns in or otherwise interpret this information.

Semi-Structured data is a cross between the two. It is a type of structured data, but lacks the strict data model structure. With semi-structured data, tags or other types of markers are used to identify certain elements within the data, but the data doesn’t have a rigid structure. For example, word processing software now can include metadata showing the author’s name and the data created, with the bulk of the document just being unstructured text.

The data that does not conform with the formal structure of data models associated with relational databases or other forms of data tables, but nonetheless contain tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data.

Structured data first depends on creating a data model - a model of the types of business data that will be recorded and how they will be stored, processed and accessed. This includes defining what fields of data will be stored and how that data will be stored: data type (numeric, currency, alphabetic, name, data, address) and any restrictions on the data input (number of characters; restricted to certain terms such as Mr., Ms. or Dr.; M or F).

By taking a holistic approach to information governance, the Infobelt Governance Platform (IGP) makes information assets accessible. Infobelt optimizes the management of information by reducing storage costs and ensuring compliance to company and regulatory policy. Infobelt has harnessed the ability to communicate exactly what amongst this information glut is essential to the business.

Learn more about what Infobelt can do for you.