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Many companies look to streamline business processes by automating business information management. However, the number of management solutions can be confusing, especially when the boundaries between the solutions are not well defined. For example, consider document management systems (DMS) and content management systems (CMS): Some people use the terms DMS and CMS as synonyms, but that is not fully correct — though they have some similar features.
In general, a DMS is a system that helps businesses to create, track and store digitized documents. A DMS is used to classify, retain and protect electronic information. It also supports versioning, collaboration and workflows. Content management systems are used to create and manage various types of digital content besides documents in the traditional sense. For example, in addition to being used for PDFs, Word files or Excel files, a CMS could be used to manage things like images, web pages, records and flash files.
CMS and DMS applications have other similarities beyond the fact that both handle digital data, but there are important differences between the two as well. Let’s take a look at the similarities and differences.
Document management systems and content management systems both do the following:
Despite the similarities, DMS and CMS tools differ in a number of ways. Each has some key features that the other doesn’t have, and they deal with different types of data. Here are some examples:
As we can see from those differences, a CMS plays a broader role than a DMS does, though a CMS typically includes at least some of the features of a DMS, because documents account for much of the digital content a CMS handles.
At the small-business level, CMS and DMS functionality may look quite similar, because small businesses don’t tend to have complex content and document management needs, so they don’t need the full range of the features and functionality available in both types of systems. In contrast, large enterprises usually use content and document management functionality to the fullest, because they need to manage a lot of structured and unstructured data.
To make the differences between the two more clear, it’s better to look at CMS and DMS from the perspective of big businesses and consider enterprise document management (EDM) and enterprise content management (ECM) systems.
Related Article: 6 Ways Document Management and Records Management Differ
Enterprise document management systems are sets of technologies designed to handle creation, capture, indexing, storage, retrieval, routing and distribution of corporate documentation. Enterprise content management, on the other hand, is a term used to refer to a set of strategies, methods and tools used to capture, manage, store, preserve and deliver corporate digital data.
As is the case with DMS and CMS, EDM and ECM overlap. Sometimes, it’s difficult to say whether they are two different systems or one entity.
ECM requires functionality capable of the following:
1. Capturing information: Creating information by digitizing paper documents, or obtaining, organizing and structuring information in electronic formats.
2. Managing information: Connecting, modifying and employing information. Specific aspects of managing information include the following:
3. Storing information: Short-term storage of files in accessible folders to allow editing of files so frequently changing information can be updated.
4. Preserving information: Long-term retention of infrequently changing information as part of regulatory compliance efforts.
5. Delivering information: Providing clients, partners or auditors with required information upon request.
A company could deploy an EDM system as a stand-alone system that would perform those functions with documents only. On the other hand, EDM could be deployed as part of an integral ECM system, with its functions limited to the “managing information” component.
Related Article: Enterprise Content Management at the Crossroads
Because of their shared functionality, EDM and ECM systems are theoretically similar. But what about in practice? Let’s compare ECM and EDM systems that co-exist in one organization. We'll use the SharePoint platform as an example, because it is suitable for both purposes. For example, let's look at how a hospital with more than 1,000 employees would implement SharePoint ECM and EDM functionality.
SharePoint Enterprise Document Management
SharePoint can be used to scan various types of contracts (payer, employment, partnership, maintenance, equipment purchase), invoices, purchase orders, certificates, patient documents, etc. with automatic verification and coding of scanned documents. It also supports automated routing of medical, financial and human resources documents to relevant personnel for review and approval, and for real-time collaboration when creating and editing documents.
SharePoint offers versioning and audit trail tracking of documents required for HIPAA compliance, and provides a wide range of permission levels to restrict access to health records, prescriptions, lab results, etc.
SharePoint ensures long-term archiving of infrequently retrieved documents (e.g. expired contracts) in document repositories in accordance with regulatory mandates. For example, HIPAA requires retention of some documents for six years.
SharePoint Enterprise Content Management
SharePoint provides indexing and categorization of various types of content (contracts, invoices, pathology reports, lab results, X-rays, ultrasounds, physician notes on CDs or DVDs), thus making it possible for information to be accurately structured and stored in folders and lists.
To support easier retrieval of information from multiple sources, SharePoint supports ECM integration with medical imaging, patient registration, electronic health records (EHR), lab systems and more. It also supports the creation and publishing of research papers, analytic data, news and marketing materials, and employee handbooks on the medical center’s website, intranet and other applications and systems. Usually, the content is in web-focused formats, such as HTML or XHTML. In addition, SharePoint supports the creation of master pages and page layouts that can be reused by content authors afterward.
SharePoint has built-in video and audio players, so video and audio files can be played directly from the medical center’s intranet.
Based on this example, we see EDM and ECM focus on different things: While EDM involves digitizing files, complying with regulations and guiding structured information through the whole cycle from creation to distribution or archiving, ECM’s main purpose is proper organization of both structured and unstructured digital assets to support accurate storage, easy retrieval and publishing of digital content.
So rather than viewing document management and content management as the same, view them as complementary. Together or alone, they can help businesses effectively manage digital information.
Sergey Golubenko is team lead and solution architect at ScienceSoft. Sergey has over13 years experience in software development, including over 7 years of working with Microsoft SharePoint.
Getty Images/iStockphoto
Secure file sharing means more than encryption to protect from would-be outsider threats — it includes protecting employees from accidentally passing sensitive information to co-workers who don’t have privileges to see it.
That’s all more complicated in the era of cloud document sharing, when files can be uploaded to collaboration platforms such as Microsoft Teams. Where does a file go by default when someone shares it in Teams? SharePoint, unless the enterprise maps it elsewhere.
“Many customers have told us that’s not what they want,” said Muhi Majzoub, executive vice president and chief product officer at OpenText, discussing the latest output of his company’s partnership with Microsoft. “The goal of the partnership is to build connectivity so that OpenText Core Content, OpenText Documentum and the OpenText Content Suite become a storage option that users can set by default.”
OpenText joins competitors — such as Box — in releasing a Teams integration where its various document clouds can provide the backbone for Teams document sharing. All the compliance and access controls users set up in Core and other OpenText secure file sharing clouds remain in place as employees share docs across Teams channels.
Microsoft cooperating with competitors on Teams document sharing is good for business, despite its own competitive interests with OneDrive and SharePoint secure file-sharing tools, said Alan Pelz-Sharpe, founder of Deep Analysis. The document cloud market is so enormous, companies such as Box and OpenText — which respectively work with medium-to-large and the largest of companies — could “grow another billion dollars and not touch each other,” he added.
Majzoub said he has not yet heard any call from OpenText customers for similar integration of its enterprise document clouds with Slack, the biggest Teams competitor. That makes sense, Pelz-Sharpe said, because many people use Slack to collaborate and not as a content repository. But that may change quickly in the future as Slack and Salesforce meld their features and capabilities.
“A lot of people use Salesforce as their system of record; that’s reality,” Pelz-Sharpe said. “Salesforce, by default, is an enormous document management system.”
OpenText released its Teams integration as part of Cloud Editions (CE) 22.2, the quarterly update to its cloud-based enterprise information management application suite. CE 22.2 also kicks off Project Titanium, an internal code name for OpenText’s development efforts to catch up its public-cloud offerings — features-wise — with its private OpenText Cloud.
More data privacy compliance tools for the U.S., Canada and Europe will be coming to public-cloud users. That’s become more important as more OpenText customers move their enterprises to particular public-cloud environments. While OpenText continues to partner closely with Google Cloud, many customers also choose AWS and Azure for their cloud, Majzoub said.
Project Titanium also includes OpenText Cloud users, as well. OpenText has released new capabilities to more quickly open new OpenText Cloud data zones for customers, when needed, to achieve parity with public cloud providers.
Other features OpenText released in CE 22.2 include tools for healthcare customers to track devices and custom reports for Risk Guard, a tool that scans networks for user-defined offensive or prohibited content.
Also released was customer information lifecycle management tools that promote regulatory compliance for financial services users. That feature comes with integrations to CRMs such as Salesforce, to enforce compliance with user policies across sales applications outside of OpenText.
Don Fluckinger covers enterprise content management, CRM, marketing automation, e-commerce, customer service and enabling technologies for TechTarget.
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Posted on August 9, 2022
Gartner has recognized Microsoft as a Leader in the 2022 Gartner® Magic Quadrant™ for Cloud AI Developer Services, with Microsoft placed furthest in “Completeness of Vision”.
Gartner defines the market as “cloud-hosted or containerized services that enable development teams and business users who are not data science experts to use AI models via APIs, software development kits (SDKs), or applications.”
We are proud to be recognized for our Azure AI Platform. In this post, we’ll dig into the Gartner evaluation, what it means for developers, and provide access to the full reprint of the Gartner Magic Quadrant to learn more.
“Although ModelOps practices are maturing, most software engineering teams still need AI capabilities that do not demand advanced machine learning skills. For this reason, cloud AI developer services (CAIDS) are essential tools for software engineering teams.”—Gartner
A staggering 87 percent of AI projects never make it into production.¹ Beyond the complexity of data preprocessing and building AI models, organizations wrestle with scalability, security, governance, and more to make their model’s production ready. That’s why over 85 percent of Fortune 100 companies use Azure AI today, spanning industries and use cases.
More and more, we see developers accelerate time to value by using pre-built and customizable AI models as building blocks for intelligent solutions. Microsoft Research has made significant breakthroughs in AI over the years, being the first to achieve human parity across speech, vision, and language capabilities. Today, we’re pushing the boundaries of language model capabilities with large models like Turing, GPT-3, and Codex (the model powering GitHub Copilot) to help developers be more productive. Azure AI packages these innovations into production-ready general models known as Azure Cognitive Services and use case-specific models, Azure Applied AI Services for developers to integrate via API or an SDK, then continue to fine tune for greater accuracy.
For developers and data scientists looking to build production-ready machine learning models at scale, we support automated machine learning also known as autoML. AutoML in Azure Machine Learning is based on breakthrough Microsoft research focused on automating the time-consuming, iterative tasks of machine learning model development. This frees up data scientists, analysts, and developers to focus on value-add tasks outside operations and accelerate their time to production.
“As more developers use CAIDS to build machine learning models, the collaboration between developers and data scientists will become increasingly important.”—Gartner
As AI becomes more mainstream across organizations, it’s essential that employees have the tools they need to collaborate, build, manage, and deploy AI solutions effectively and responsibly. As Microsoft Chairman and CEO Satya Nadella shared at Microsoft Build, Microsoft is "building models as platforms in Azure" so that developers with different skills can take advantage of breakthrough AI research and embed them into their own applications. This ranges from professional developers building intelligent apps with APIs and SDKs to citizen developers using pre-built models via Microsoft Power Platform.
Azure AI empowers developers to build apps in their preferred language and deploy in the cloud, on-premises, or at the edge using containers. Recently we also announced the capability to use any Kubernetes cluster and extend machine learning to run close to where your data lives. These resources can be run through a single pane with the management, consistency, and reliability provided by Azure Arc.
“Vendors and customers alike are seeking more than just performance and accuracy from machine learning model. When selecting AutoML services, they should prioritize vendors that excel at providing explainable, transparent models with built-in bias detection and compensatory mechanisms.”—Gartner
At Microsoft, we apply our Responsible AI Standard to our product strategy and development lifecycle, and we’ve made it a priority to help customers do the same. We also provide tools and resources to help customers understand, protect, and control their AI solutions, including a Responsible AI Dashboard, bot development guidelines, and built-in tools to help them explain model behavior, test for fairness, and more. Providing a consistent toolset to your data science team not only supports responsible AI implementation but also helps provide greater transparency and enables more consistent, efficient model deployments.
Microsoft is proud to be recognized as a Leader in Cloud AI Developer Services, and we are excited by innovations happening at Microsoft and across the industry that empower developers to tackle real-world challenges with AI. You can read and learn from the complete Gartner Magic Quadrant now.
References
¹Why do 87 percent of data science projects never make it into production? Venture Beat.
Gartner Inc.: “Magic Quadrant for Cloud AI Developer Services,” Van Baker, Svetlana Sicular, Erick Brethenoux, Arun Batchu, Mike Fang, May 23, 2022.
Gartner and Magic Quadrant are registered trademarks and service marks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Microsoft. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
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