Freely subscribe to our NEWSLETTER

Information Lifecycle Management (ILM) has been hyped in the last few years and is seen by many as a revolutionary approach to optimising business performance from the inside. It also is in danger of being perceived as a panacea for all business and IT challenges that can be implemented right now.

The reality is in fact quite different, as true ILM is still many years away, with a recent SNIA survey finding that one of the four most common ways of losing information is not being able to interpret it properly – a problem ILM is intended to overcome. The key to appreciating the hurdles that still need to be overcome lies in seeing the difference between information and data. Data is defined as the raw codes and figures that make up any document or application. This data becomes information when it is put into context, and its value and meaning can change, depending on that context. This was explained by Hitachi Data Systems’ Chief Technology Officer, Hu Yoshida, in a recent blog posting (Storage, Data, Information). He pointed out how one hotel breakfast receipt, containing figures such as the meal cost, the customer’s room number and the amount left as a tip for the server, can provide different information to the customer, the server and the hotel management.

An IT system works with data. Information, as we have seen above, is a much more subjective and subtle concept – something that is simple for humans to understand, but not so for machines without further references and tools. Establishing a set of rules and processes that govern business and IT operations based on the value of information, then, is correspondingly complex. This challenge is exacerbated by the fact that many organisations are now required to store their data for long periods (sometimes more than 100 years), so best practices need to be in place not just to handle the data held now, but to scale as this resource grows.

This article aims to clarify the link between ILM and Data Lifecycle Management (DLM) and explore what organisations should be doing now to optimise their business processes with the available technology while facilitating future development.

ILM:DLM – What’s the difference?

DLM is the combination of services and solutions that help CIOs and IT managers deliver adequate data management services to any given application environment. This includes protecting data, moving it around, and presenting it to that environment - activities that are tightly connected with managing the different storage resource profiles. Exactly what needs to be done varies depending on the application that the data is being used by (such as email, databases or CRM (Customer Relationship Management) software).

The idea that data is used differently and can have a different meaning in these various environments is at the heart of the ILM concept, where the value of information in a given, environment is automatically understood, and processes are carried out accordingly.

Information cannot exist without the data that underpins it, so ILM relies on DLM processes to effectively fit in with the IT infrastructure while also addressing changing business priorities. While the two concepts are closely connected, ILM is characterised by rules that can be set to optimise the IT infrastructure in order to better manage the business. It incorporates various IT processes, such as data classification, storage resource management, compliance and security and connects with business process management. ILM also has more direct connection with the application layer than DLM.

As both concepts mature over time, we’ll see that there are fewer arguments over the differences between ILM and DLM, as one is a subset of the other. It is more important to recognise that DLM is the first pragmatic step towards the ILM of the future.

Who is DLM right for?

DLM is an effective enabler of improved management within the IT infrastructure for data storage resources and services. As this is a key business need for all industry segments, DLM has become popular in many vertical markets.

Even where a defined DLM strategy has not been adopted, general management practices put in place around storage mean that many IT departments have deployed DLM even if only partially. It has become wide-spread mainly due to the fact that it enables better alignment of data storage and management practices with key enterprise applications, helping to drive IT towards business process management objectives – an important aim for all CIOs and part of the eventual ILM vision.

Where should we be aiming?

ILM has generated a lot of hype due to the implications it has for enabling IT to drive better efficiency and business performance and it can be defined as automatically handling and channelling any piece of information from wherever it resides in the IT infrastructure to where it is needed to meet business requirements. Combining all the IT concerns already mentioned to achieve concrete ILM is a complex goal that has not yet been realised. Indeed, it is likely to be another five to ten years before we are able to realise true ILM: understanding and harnessing the interaction between business applications and the rest of the IT stack.

What most of the industry sees as ILM at the moment is in fact DLM – controlling the movement of data across the storage hierarchy depending on its value to the business at a given point in time (and, in Hitachi Data Systems’ case in all directions).

Traditionally content is moved down the storage hierarchy as it ages, but it is important to bear in mind that the most important piece of information in any organisation is the one needed for the next business evolution. This might be in an email received this morning, or in an old report written two years ago and DLM ensures that wherever the answer is, it is easily accessible when required.

By introducing rules to relate the movement of data up and down the stack to application demands, companies are incorporating a link with business process management as well, but not equivalent to ILM practices. While DLM can be related to business on an application requirement level, ILM will do so on a business information level.

The bottom line is that managing information is much more complex than managing data. While the industry should be looking towards ILM as a future goal, the technology available today means that DLM is currently more achievable and should be approached as the first step in the process.

Creating a platform for evolution

Driving IT towards enabling ILM, businesses need to ensure their application and storage environments understand the significance of the data they work with, and therefore how it should be globally handled. Effective metadata tagging of data allows the tracking of all relevant management criteria, which is a fundamental requirement for DLM. As metadata control becomes more sophisticated and access to application layers is improved, the ILM framework will become easier to implement.

The lifecycle right from creation in the application layer through to archiving (and potentially back again) and ultimately to deletion needs to be managed. The management of the lifecycle process, creating a bridge between several layers of IT and business management, can be problematic for enterprises and at this stage it is difficult to say how the infrastructure needs to evolve in order to facilitate it.

A simple and efficient approach for now is to ensure they have an effective DLM strategy in place to act as a foundation for future developments. By getting to grips with the concepts surrounding these issues now and taking steps to implement DLM processes, IT managers can ensure their businesses are on the road to ILM.

IT managers can follow four steps to mastering the DLM/ILM challenge:

1. Ensure the executive team and IT department both understand the difference between ILM and DLM as well as their potential benefits, and recognise what is currently achievable

2. Encourage all relevant business departments to collaborate in setting information management requirements and creating a plan to bridge the gap between business process management and IT management. This in turn will align the two areas to address the same goals

3. Identify which applications are most valuable and business-critical to your organisation, and agree how the associated data should be treated

4. Work with vendors to develop a cohesive IT stack that maximises the efficiency enabled by DLM while providing flexibility for further ILM developments in the future

How can Hitachi Data Systems help?

Hitachi Data Systems already supplies a wide range of customers with tiered storage management solutions that facilitate DLM processes.

Hitachi Universal Volume Manager software enables the virtualisation of multi-tiered storage area networks made up of heterogeneous storage systems. Combined with Hitachi Volume Migration software, it provides an automated data lifecycle management solution, across multiple tiers of storage.

Hitachi HiCommand® Tiered Storage Manager software helps users define and dynamically migrate data across multi-dimensional tiers of storage without disruption to the application layer.