Are Master Data Management and Hadoop a Good Match?

Master Data is the critical electronic information about the company we cannot afford to lose. Accordingly, we should sanitise it, look after it, and store it safely in several separate places that are independent of each other. The advent of Big Data introduced the current era of huge repositories ?in the clouds?. They are not, of course but at least they are remote. This short article includes a discussion about Hadoop, and whether this is a good platform to back up your Master Data.

About Hadoop

Hadoop is an open-source Apache software framework built on the assumption that hardware failure is so common that backups are unavoidable. It comprises a storage area and a management part that distributes the data to smaller nodes where it processes faster and more efficiently. Prominent users include Yahoo! and Facebook. In fact more than half Fortune 50 companies were using Hadoop in 2013.

Hadoop – initially launched in December 2011 ? has survived its baptism of fire and became a respected, reliable option. But is this something the average business owner can tackle on their own? Bear in mind that open source software generally comes with little implementation support from the vendor.

The Hadoop Strong Suite

  • Free to download, use and contribute to
  • Everything you need ?in the box? to get started
  • Distributed across multiple fire-walled computers
  • Fast processing of data held in efficient cluster nodes
  • Massive scaleable storage you are unlikely to run out of

Practical Constraints

There is more to Hadoop than writing to WordPress. The most straightforward solutions are uploading using Java commands, obtaining an interface mechanism, or using third party vendor connectors such as ACCESS or SAS. The system does not replace the need for IT support, although it is cheap and exceptionally powerful.

The Not-Free Safer Option

Smaller companies without in-depth in-house support are wise to engage with a technical intermediary. There are companies providing commercial implementations followed by support. Microsoft, Amazon and Google among others all have commercial versions in their catalogues, and support teams at the end of the line.

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A Definitive List of the Business Benefits of Cloud Computing ? Part 4

Lowers cost of analytics

Big data and business intelligence (BI) have become the bywords in the current global economy. As consumers today browse, buy, communicate, use their gadgets, and interact on social networks, they leave in their trail a whole lot of data that can serve as a goldmine of information organisations can glean from. With such information at the disposal of or easily obtainable by businesses, you can expect that big data solutions will be at the forefront of these organisations’ efforts to create value for the customer and gain advantage over competitors.

Research firm Gartner’s latest survey of CIOs which included 2,300 respondents from 44 countries revealed that the three top priority investments for 2012 to 2015 as rated by the CIOs surveyed are Analytics and Business Intelligence, Mobile Technologies, and Cloud Computing. In addition, Gartner predicts that about $232 million in IT spending until 2016 will be driven by big data. This is a clear indication that the intelligent use of data is going to be a defining factor in most organisations.

Yet while big data offers a lot of growth opportunities for enterprises, there remains a big question on the capability of businesses to leverage on the available data. Do they have the means to deploy the required storage, computing resources, and analytical software needed to capture value from the rapidly increasing torrent of data?

Without the appropriate analytics and BI tools, raw data will remain as it is – a potential source of valuable information but always unutilised. Only when they can take the time, complexity and expense out of processing huge datasets obtained from customers, employees, consumers in general, and sensor-embedded products can businesses hope to fully harness the power of information.

So where does the cloud fit into all these?

Access to analytics and BI solutions have all too often been limited to large corporations, and within these organisations, a few business analysts and key executives. But that could quickly become a thing of the past because the cloud can now provide exactly what big data analytics requires – the ability to draw on large amounts of data and massive computing power – at a fraction of the cost and complexity these resources once entailed.

At their end, cloud service providers already deal with the storage, hardware, software, networking and security requirements needed for BI, with the resources available on an on-demand, pay-as-you-go approach. In doing so, they make analytics and access to relevant information simplified, and therefore more ubiquitous in the long run.

As the amount of data continues to grow exponentially on a daily basis, sophisticated analytics will be a priority IT technology across all industries, with organisations scrambling to find impactful insights from big data. Cloud-based services ensure that both small and large companies can benefit from the significantly reduced costs of BI solutions as well as the quick delivery of information, allowing for precise and insightful analytics as close to real time as possible.

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Succeed at Transformation

Despite the pomp and fanfare associated with launching corporate transformation programs, in reality very few of them succeed. According to a recent report by McKinsey the success rate is pegged below 40%. In addition, the same research indicates that defensive transformations – those undertaken as part of crisis management – have lower chances of success than progressive ones – those launched to streamline operations and foster growth. However, adopting certain strategies, like setting clear and high goals, and maintaining energy and engagement throughout the implementation phase, can really boost the project’s success rate. A key aspect of business transformation is IT transformation. This can be attributed to the fact that significant business change is either driven or influenced by technological change.

So what is IT Transformation?

IT transformation is basically a holistic reorganisation of the existing technological infrastructure that supports the company’s mission critical functions. In essence, IT transformation is not all about effecting change for the sake of change but involves systematic steps that align IT systems to business functions. To appreciate this approach, it is important to explore current trends in the business world where human resource, finance and IT transformations are being carried out in unison. This is being done to develop strong corporate centres that are leaner, agile and more productive that enhance greater synergies across all business functions.

IT transformation inevitably results in major changes of the information system’s technology, involving both hardware and software components of the system, the architecture of the system, the manner in which data is structured or accessed, IT control and command governance, and the components supporting the system. From this scope of works it is evident that IT transformation is a huge project that requires proper planning and implementation in order to succeed.

Tips to Improve Success in IT transformations Projects

1. Focus on Benefits not Functionality

The project plan should be more focused on benefits that can be accrued if the system is implemented successfully rather than system functionality. The benefits should be in line with business goals, for instance cost reduction and value addition. The emphasis should be on the envisaged benefits which are defined and outlined during the project authorisation. The business benefits outlined should be clear, feasible, compelling and quantifiable. Measures should be put in place to ensure that the benefits are clearly linked to the new system functionality.

2. Adopt a Multiple Release Approach

Typically most IT projects are planned with focus on a big launch date set in years to come. This approach is highly favoured because it simplifies stakeholder expectation management and avoids the complexity associated with multiple incremental releases. However, this approach misses the benefit of getting early critical feedback on functioning of the system. In addition, the long lead times often result in changes in project scope and loss of critical team members and stakeholders. IT transformation projects should be planned to deliver discrete portions of functionality in several releases. The benefit of multiple release approach is that it reduces project risks and most importantly allows earlier lessons learnt to be incorporated in future releases.

3. Capacity of the Organisation to confront Change

As pointed out, IT transformations result in significant changes in business operations and functions. Hence it is important that all business stakeholders should be reading from the same script in regards to changes expected. In addition, key stakeholders should be involved in crucial project stages and their feedback incorporated to ensure that the system is not only functional but business focused.

Transformation to a process based organisation

Today’s global marketplace rewards nimble organisations that learn and reinvent themselves faster than their competition. Employees at all levels of these organisations see themselves as members of teams responsible for specific business processes, with performance measures tied to the success of the enterprise. As team members, they are “owners” of the process (or processes) to which they are assigned. They are responsible for both the day to day functioning of their process(s), and also for continuously seeking sustainable process improvements.

Transforming a traditionally designed “top down control” enterprise to a process-based organisation built around empowered teams actively engaged in business process re-engineering (BPR) has proven more difficult than many corporate leaders have expected. Poorly planned transformation efforts have resulted in both serious impacts to the bottom line, and even more serious damage to the organisation’s fabric of trust and confidence in leadership.

Tomislav Hernaus, in a publication titled “Generic Process Transformation Model: Transition to Process-based Organisation” has presented an overview of existing approaches to organisational transformation. From the sources reviewed, Heraus has synthesised a set of steps that collectively represent a framework for planning a successful organisational change effort. Key elements identified by Hernaus include:

Strategic Analysis:

The essential first step in any transformation effort must be development of a clear and practical vision of a future organisation that will be able to profitably compete under anticipated market conditions. That vision must be expected to flex and adjust as understanding of future market conditions change, but it must always be stated in terms that all organisational members can understand.

Identifying Core Business Processes:

With the strategic vision for the organisation in mind, the next step is to define the core business processes necessary for the future organisation to function. These processes may exist across the legacy organisation’s organisational structures.

Designing around Core Processes:

The next step is development of a schematic representation of the “end state” company, organised around the Core Business Processes defined in the previous step.

Transitional Organisational Forms/ Developing Support Systems:

In his transformation model, Hernaus recognises that information management systems designed for the legacy organisation may not be able to meet the needs of the process management teams in the new organisation. Interim management structures (that can function with currently available IT system outputs) may be required to allow IT professionals time to redesign the organisation’s information management system to be flexible enough to meet changing team needs.

Creating Awareness, Understanding, and Acceptance of the Process-based Organisation:

Starting immediately after the completion of the Strategic Analysis process described above, management must devote sufficient resources to assure that all organisation members, especially key managers, have a full understanding of how a process-based organisation functions. In addition, data based process management skills need to be provided to future process team members. It is not enough to schedule communication and training activities, and check them off the list as they are completed. It is critical that management set behavioural criteria for communication and training efforts that allow objective evaluation of the results of these efforts. Management must commit to continuing essential communication and training efforts until success criteria are achieved. During this effort, it may be determined that some members of the organisation are unlikely to ever accept the new roles they will be required to assume in a process-based organization. Replacement of these individuals should be seen as both an organisational necessity and a kindness to the employees affected.

Implementation of Process Teams:

After the completion of required training AND the completion of required IT system changes, process teams can be formally rolled out in a planned sequence. Providing new teams with part time support by qualified facilitators during the firsts weeks after start-up can pay valuable long term dividends.

Team Skill Development and Continuous Process Improvement:

Providing resources for on-going skill development and for providing timely and meaningful recognition of process team successes are two keys for success in a process-based organisation. Qualified individuals with responsibility for providing training and recognition must be clearly identified and provided with sufficient budgetary resources.

The Hernaus model for transformation to a process based organisation is both well thought out and clear. His paper provides an ample resource of references for further study.

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