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Digital Asset Management


Management of digital assets is a task of managing digital assets. It is a system which includes hardware and software computer systems for aiding the digital management processes. It is referred as a protocol of downloading, backing up, grouping, maintaining, exploring and optimizing files. The simple definition of Digital Management Assets (DAM) is that it allows storage, retrieval and distribution of images, videos or other digital media. DAM does allow easy tracking of assets and one does not spend a lot of time searching for assets. It takes control of the client’s brand image. When the environment contains additional information outside the file, the digital file may eventually become an asset. For an asset to be useful, it must be accessible for its intended purpose. The only way that would make it possible is the metadata, which is the descriptive information for the files which makes up an asset.

The metadata document is written by people for aiding a dataset collected. Most of metadata resources are available on the websites. The metadata document provides a simple working level of view for the needs, issues and processes for a specific discipline. It tries to avoid online resources listing that might move the location. The web is ever evolving as a pool of resources. The metadata document is applied to anything but it is possible to describe exactly a file on a computer the way one can describe a piece of art design of a wall or describe an area using a map. However, the only differences are in the metadata content. This is because it provides snippets of information, which have a particular meaning (Philips 2004, p. 45). This information is in relation to a certain piece of work. The information can be treated as well as managed like any other form of information. This depends on the way it was created or stored. The metadata document has a little value of its own and it adds value to other information. 


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The metadata is created because it enhances the use of data. Thus, when creating or collecting the data, it is vital to take into consideration the way that data would be used across the whole research cycle. The first step is where to collect data from for a specific project when carrying out a research. Data formats such as text can be indexed and then searched in the website through the use of computers. Another step is using data whereby one needs to understand the way data can be structured, things that it describes and the way it was collected. This calls for a more description of the process that led to data. Lastly, preserving and data re-use is another thing that should be taken into consideration. Finding and using data is the same, but preserving it is different because of future needs. Data can be preserved for future re-use; thus, it should be carefully stored for data loses its credibility and value. 

The metadata is viewed from the way it performs its functions and various activities support data use. The metadata are categorized in different types. One of them is the scientific metadata. This is the specific information of the study, which needs interpretation of data collected. This type of data is very discipline, specific, and it requires some knowledge of the sphere (Deshmukh 2006, p. 125). The other types of metadata are broadly administrative in nature and they deal less in science. However, they deal more with the process of the way data came to be and the way it should be managed. The most common types of this kind of data include the provenance metadata. This relates to original data and it ranges from human to technical. Another one is the rights and access metadata, which provides significant information about access and rule usage. The preservation data is another data, but this data builds the history from provenance. This data includes information vital for building a sense of trust in the data collected. The last one is the structural data, which provides significant information to a computer or a person reading the data.

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Some major components need to be taken into consideration when planning about metadata collection and management. One is attaching the metadata to a row data, which is collected from various groups of people. Sometimes the metadata can be individually or quite independent. This leads to item-level idea, which describes the individual. The collection-level metadata is a description of the collected items, which have some commonalities. Dealing with collection-level data is beneficial because less efforts and risks are involved. However, it limits individuals from discovering more data from a lager collection area (Hellen Hockx-Yu 2006, p. 243). For instance, finding a library where one can gather information is easy. However, finding a book which one wants may be difficult. Apart from the collection and item levels, there is another level, which is known as the sub-item. This increases the efforts required but it allows one to search better and it saves time.

There are broad categories of digital asset management systems. One of them is brand asset management system, which focuses on content re-use facilitation in the large organizations. In this system, the content is meant for marketing or sale related activities such as imagery products, logos and collateral marketing. The second one is library asset management system which focuses on storage activities. Additionally, it aids in a retrieval of infrequency changing media assets such as photo as well as video archives. The last one is production asset management system, which focuses on managing assets being created for digital media production such as animation, 3D feature film and many others. The DAM software system may be an open source and its providers are the enterprise level solutions. They often scalable as well configure products, which handle a variety of assets. The enterprise system may include the customized products added to the base system or custom-development, which matches with the workflow of an organization.

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Digital asset management is divided into sub-categories. One of them is the media asset management (MAM). This is a system which is concerned with audio, video and other contents of media. Another one is an enterprise content management (EMC) that deals with solutions, thus, addresses analogous features in a wider industrious area. Additionally, it is easier to categorize the smaller DAM system as content because they operate in a specific operational content (Ross 2004, p. 228). This is especially the systems, which are attached to audio or video productions. The major differentiator in this case is the decoder types and the input or output for asset ingest and outgest. The metadata serves as play-out of guiding decoders, transcoders and inputs to access control rules in essence. Therefore, essence is treated as non-described and storage object for viewing or editing. There are some relevancies when considering entire design and the larger implementation. The more the technical architecture would need to accommodate delivery requirements.

The ECM is one of the forms of digital management, which is a formalized means of organizing and storing documents and other contents in the organization. The EMC is a form of content management, which combines the capture, document networking, digital driving, data management and workflow. It includes challenges involved in using as well as preserving the internal unstructured information of the company. Thus, most ECM solutions focus on business to employee system. The ECM solutions evolved, thus, new components emerged. For instance, the content is checked in and out and each use generates new metadata of the content. The information of how and when the content used can allow the system to acquire new filtering and retention of rule decisions.

DAM is beneficial for creative workflows and marketing operations. This is because it fosters brand consistency across all clients. Moreover, it saves time when fulfilling requests for photos, presentations and marketing materials in order to improve the productivity of employees. Another benefit is that it manages and improves accountability of brand assets for larger brand control. The DAM helps in managing and distributing videos in order to capitalize on the increasing demand for online video without immense capital investments. It accelerates production timeline for multiple channels, thus reducing costs (Zorich 2000, p. 112).). Moreover, the DAM empowers sales channels, thus customizing and localizing sales in order to effectively increase sales. Lastly, it slashes the manual labor costs as well as consumables, thus, improving efficiency through automating several wearisome processes at once.

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            The assets managed are collected and stored in digital format system. The process involved in the collection and storing system is referred as essence. This is the representation of the highest fidelity and the highest resolution. The detailed information of the assets is done through metadata. The metadata is defined as the asset and depth description, which varies depending on system needs, designer or user. The metadata describes but it is not limited to asset content description through encoding or decoding means. Some predefined standards as well as metadata templates exist including the Dublin Core and PBCore. Usually, there are related proxy essence copies such as MPEG 2 and JPEG2000 for images and vide especially when the system contains a large size asset essence. A copy of proxy is a representation of lower resolution essence used for referencing in order to reduce the overall bandwidth DAM system infrastructure requirement. The DAM software system generates and retains asset ingestion at a time or it can be generated through the transcoders.

The transcoding is the method of conversing or encoding message from one digital to another as such as in the case of the movie and audio files. The transcoding process is done especially when a target device does not maintain the format or when there is a limited storage capacity. This occurs when there is a file searching for presentation. For example, the DPX files are widely used in digital cinema as a common format, but the file size of a movie which is 8 terabytes takes two hours. In case the size is large, it will increase the cost and even making it difficult to handle the movie files. The transcoding of JPEG2000 format has a better comprehension than the coding technologies thus it compresses images into a half-size. The transcoding generates a loss because it is a lossy process, although it can be lossless when the input is losslessly compressed. The process of lossy to lossy transcoding process brings about lossy generation varying degrees. In other words, the lossy transcoding of the uncompressed transcoding is technically lossless since information does not get lost in the process. However, the process is irreversible thus called a destructive process.

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The most common transcoding process is a two step process whereby the original data file is decoded into an immediate uncompressed format such as audio PCM or video YUV. Additionally, the transcoding may involve direct changing assembled software code in order to work on varied platform or operating system. It is recommendable to use source code and recompile the application but sometimes it is impractical or impossible when doing so. This is especially when the source code in not available. Additionally, one may re-encode data through the use of the same format for various reasons. One of the reasons is the need to edit data in a compressed format such as image editing performance on a JPEG. One may decode, edit and re-encode the images. The re-encoding contributes to digital generation loss. Thus, in case one may wish to repeatedly edit a file, decoding should only be done once. In case there is a need for encoding to a lossy format, the file would be suspended until finalization of data is done. Another reason is image scaling whereby pictures are changed in a sizeable way through a transsizing process (Ross 2004, p. 229). The process is used in case the production resolution diverges from the media motion. 

DAM occurs in varied forms such as images, audios, videos, logos, presentations and documents. However, have in case an organization own asset does not necessarily mean that they have value in their organization. However, they can only know that their assets have value when they have found and used it when needed. Thus, use of CQ5 DAM makes it easy for one to find, share, publish and add comments in spite of any format. Moreover, the CQ5 DAM utilizes accessible repositories for shared and permissions based access to digital media assets. It utilizes the web based shared workspaces for workflow based idea sharing, thus, provides full services for marketing materials, video and images. However, the hidden costs in digital management are evidenced through operational redundancy, graphic recreations or asset duplicate versions. It is vital to protect the brand integrity especially on a fast paced business. In order to manage high intellectual properties, it is vital to improve metadata accuracy constantly, keep audit trails and control inter-enterprise access.

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Valuing digital assets is crucial because every modern marketer is tasked with creating, and delivering market materials in order to support the advancement of the brand as well as facilitate revenue growth. Thus, they need the DAM systems in order to manage better their business. DAM software tools are becoming a necessity in many organizations because they help in balancing at least some of the consuming projects (Tozer 2000, p. 69). In addition, many assets have a diminishing marginal value because as one keeps investing, the return diminishes gradually. Therefore, one does not necessarily value the assets in case it is build from scratch. However, the assets are valued basing on incremental disinvestment. Thus, drive firm value should be converted into cash flow projections including incremental investments in the DMA in order to increase the enterprise value. When valuing digital assets, one may be required to determine how much business owner willing to pay in repairing or replacing the digital asset in case it was damaged or disabled.

The DAM is valuable for global marketing. The global marketing is usually a challenge regardless of the company size, thus, DAM is a valuable tool in the global a marketing. In order to communicate effectively with the clients, the marketers should ensure that they have a right content in the right format. The right content means the use of pictures, videos, audio and pictures should be appropriate in order to send a clear message to customers. Having the right content for a particular region is a challenge. Marketers use images, graphics as well as videos in communicating the message across to customers. However, creating this content requires proper the implementation plan. This is because implementation of DAM is a challenge; thus it should be carefully implemented. Many of the organization using market content are not under the management. Thus, everyone should be involved when implementing the content, thus avoiding the challenges that may arise.

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One of the challenges of dealing with digital assets is that some of the digital assets such as videos and images are difficult to manage than text based documents. This is because they may not include any text at all, hence difficult to search. The DAM presents many challenges especially managing the traditional text-based content. This is because digital assets are often located on different repositories. Moreover, they are handled by multiple groups in an organization, and they are handled differently. Lastly, they are not tagged with standardized metadata. While most of the software tools are built to handle digital assets, they may not help one to achieve their content management goals unless they have a long-term digital asset management strategy. It is vital for the DAM consultants to help the company deal with the challenges of DAM from a holistic perspective because they might pose a threat to an organization. They should be the major issues such as the DAM taxonomy, management of asset lifecycle and focus on the overall strategy (NISO 2004, p. 340).

Another challenge is the broadening set of devices as well as channels from, which the audience may wish to consume the content. The marketer should plan the way through, which the brand consistency should be maintained not only across the region, but also across the web, devices, videos and prints. They should ensure that they have the right tool that will help them to manage consistency. Therefore, the marketing team should manage the overall brand consistency and maintain the consistency across the web, print. DAM provides a backbone infrastructure for managing complex, creation of interrelated content and delivery processes if well implemented (Philips 2004, p. 56). However, if the broadening sets of devices are not well managed and implemented, they may hinder the organization for better performance. This is because of the challenges that they may pose to the company.

In order to manage challenges, a decision support system (DSS) may be employed on handling the challenges. The DSS is a way of modeling data, thus, making quality decisions basing on it (Laudon and Laudon 2002, p. 45). In business, making the right decision base on quality data, and one’s ability to sift through as well as analyze data.  This is done in order to find trends and solutions in the process. The DSS is a model used in data collection, analyzing data and shaping data collected for quality purpose. It makes sound decisions and constructs strategies from the analysis. Although, computers and artificial intelligence work, the ultimate goal of a human being is to execute the strategies or formulate the data into a usable hypothesis.

There are varied types of DSS models. The DSS does not have a generally accepted model, but there are varied theories to help unpick and manage these challenges. For instance, the DSS models are classified as passive, active and cooperative models. The passive mode is a system that collects data and organizes it effectively. This model does not suggest a specific decision, but it reveals the data. On the other hand, active data actually performs the function of data processing and explicitly reveals the solutions based upon the data. Since there are varied systems that are active, many companies do not trust their computer model without human intervention. Thus, a cooperative DSS is made when the data is collected, analyzed, and handed to humans who help the system to refine the data. In this case, both computer and human intervene, thus work together in order to come up with the best solution.

While the above discussed models consider the user’s relationship, there are other recent and modern models. This includes the driven DSS such as the communications driven, data driven, document driven and knowledge driven models. The driven DSS is whereby different people collaborate in order to come up with a strategy or solution. The model is usually found in the websites or in the offices. The data driven model emphasizes on the collected data, and it is then manipulated in order to fit the needs of the decision maker. This data can either be internal or external, and it is produced in different formats. It is imperative to collect data and categorize it sequentially. A document driven model uses different documents such as text documents, spreadsheets, and data base documents in order to formulate decisions as well as manipulate the information to refine strategies. Lastly, the knowledge driven model employs a special rule, which is stored in a computer in order to determine if the decision should be made or not.

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One of the valuable assets is knowledge. Knowledge is a fundamental asset in management (Hellen Hockx-Yu 2006, p. 235). Organizations need to measure their valuable assets perhaps knowledge. However, measuring the value of knowledge is quite challenging. Several methods have emerged in order to measure the intellectual capital. Many organizations are now trying to tackle the problem of intangible measurements. The recent study reveals that many organizations are now addressing the issues of management and measurement of intangible assets such as knowledge. This is because of the varied benefits. One of the benefits is that it reflects the actual worth of the company. Moreover, the measurement process provides insight into the drivers of sustainability. Lastly, it provides more important information to the potential investors.

There is need to audit data assets in order to effectively manage data holdings and realize fully their potentials in an organization. Therefore, organizations must be fully aware of the location, condition and value of assets. Conducting data audit will raise awareness of the collected data issues and improve the overall strategy. Therefore, an audit would highlight duplication of effort and areas, which requires additional investment. This will allow organizations to put their resources to the best use. The audit data assets would also highlight inadequacies of creating data and provide suggestions for policy changes, thus lessening the risks faced. A knowledgeable organization about data issues would be in apposition of maximizing the value of its collections through the continued use. In broad speaking, auditing data assets is crucial because it enables organization to prioritize resource, which will lead to efficiency savings. Another benefit is that the organization will realize the price of data through enhanced admission and recycle. Lastly, ability for managing risks is associated with loss of data, and irretrievable.

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Use of data quality assessment framework is vital because it identifies the quality related features of governance statistical systems, processes and statistical products (DQAF). The DQAF provides a structure for assessing existing practices including the internationally accepted methodologies. The framework is organized around the set of prerequisites, and data quality dimensions (Gregory 2006, p. 54). The DAF methodology is accuracy, reliable, serviceable and accessible. Additionally, auditing data assets provide information through identifying valuable data assets. This ensures that resources are not wasted in managing unnecessary assets. Data can be disposed or moved into more cost-effective offsite storage. The information gained from auditing process may assist in forward planning. This gives a more realistic idea of infrastructure and storage management. Further efficiency savings can be achieved through creating a centralized data management system (Deshmukh 2006, p. 215).

Digital Curation Centre (DCC) provides information for Digital Curation. It makes accessible the best practices for creation, management as well as preservation of digital data for use and re-use over time. The ever-increasing data quantities produced in digital form, and the way data are changing creates challenges in data Curation (Beagrie and Greenstein 2000, p. 78). Data is selected or preserved, thus, there is a need for data appraisal and selection. However, scalable and defensible data is lacking for digital preservation. The Digital Curation practitioners have designed digital manuals that will help data curators, creators and re-users of data to better understand as well as address the challenges they face. This will help them to fulfill the roles they play in data creation, management and preservation of digital data. Additionally, appraisal and selection are vital because they maintain access to all data indefinitely. Thus, data curators should make decisions about what to preserve and provide information to data access and the long term record survival (Addis, Beales, Lowe, Middleton, Norlund and Zlatev 2009, p.30).

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In conclusion, digital data management allows storage, retrieval, and distribution of images, videos or other digital media. The only way that would make it possible is the metadata, which is the descriptive information for the files making up an asset. The metadata is created because it enhances the use of data. Thus, when creating or collecting the data, it is vital to take into considerations the way that data would be used across the whole research cycle. Moreover, managing the digital assets is quite challenging, and this is when it is not well implemented. In order to manage challenges, a decision support system (DSS) may be employed on handling the challenges. Use of data quality assessment framework is vital because it identifies the quality related features of governance statistical systems, processes, and statistical products. Data is selected and preserved, thus, there is a need for data appraisal, and selection for future use.



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