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Richard Davies wrote: The UK has a good crop of technology pioneers in cloud computing - for example ElasticHosts, FlexiScale, Flexiant, OnApp - and also some strong government initiatives such as G-Cloud. We will have to see whether this kind of technical leadership converts into swift mass-market adoption or not.
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In many cases, the end of the year gives you time to step back and take stock of the last 12 months. This is when many of us take a hard look at what worked and what did not, complete performance reviews, and formulate plans for the coming year. For me, it is all of those things plus a time when I u...
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Managing Enterprise Data Complexity Using Web Services: Part 2
Developing enterprise digital dashboards using data services architecture

Enterprises are increasingly feeling the need for shorter lead time for decision making, the need to extract and present KPI (Key Performance Indicators) to management, and the need for enhanced response capability. These business needs are not in sync with the technological challenges such as the presence of heterogeneous technologies and disparate enterprise systems (e.g., ERP, SCM, CRM, etc.). This situation gets complicated with the increasing number of mergers and acquisitions resulting in the various business units within an enterprise having their own data warehouses. Adding to this is the increasing number of users inside and outside the enterprise who need real-time access to information.

In such a scenario, an EDD (Enterprise Digital Dashboard) would improve the lead time and quality of decision making by extracting and generating KPIs from enterprise software systems. The EDD is in many ways similar to an automotive dashboard, which provides for the driver a single view of the state of the automobile. Development of an EDD involves extracting and generating metrics, indicators, sales figures, production of certain product lines, identifying lead times, inventory levels, and other key organizational data from the enterprise software systems. Dashboards present critical data about the enterprise to the most significant powers who make very strategic decisions based on this information. Therefore, the quality and timeliness of this data cannot be overemphasized. The most fundamental issue is one of data integration and data rationalization across a variety of applications, databases, and technologies. In this article we present an overview of the architecture for developing enterprise digital dashboards.

Challenges
EDDs are difficult to implement due to the complexities involved in combining and calculating data from disparate business and enterprise systems such as SAP, i2, etc. Moreover there are associated problems related to the duplication of data that require data synchronization. Multiple systems in different lines of business access data in different ways depending on their needs and specific technologies. There are no consistent practices or techniques in place for the access and update of data. Apart from this, the same data element may be stored and accessed in multiple formats in different databases. The critical factor in the development of an enterprise dashboard is the fact that a dashboard is fundamentally a representation of core business data in multiple formats. These data elements may be rolled up to different levels of granularity depending on the audience in question. Therefore, one of the fundamental issues in the development of a dashboard boils down to the ease of obtaining quality data from a variety of sources. The key architectural requirements in the development of an enterprise-level dashboard include:

  • Guaranteeing data quality given the nature of the audience
  • The ability to integrate data sources in a loosely coupled manner
  • The ability to provide a unified view of information persisted across varied data sources
  • Buying instead of building - use proven commercial/open source products/frameworks instead of building from scratch
Architectural Options for the EDD: Web Services
Integration solutions from EAI vendors involve large initial investments. Moreover, the EAI products are not very flexible, do not fully support incremental investments, and are of proprietary nature. Furthermore it is not easy to work with EAI systems while integrating with IT systems of different partners with heterogeneous systems. All of the aforementioned problems need to be addressed while implementing a Web services-based EDD solution. This is because the solution should be able to interact with various systems, should be flexible, should support incremental investments, and should be able to interact with the systems of the firm's partners. Web services address most of the problems mentioned above. Web services would support the data coming from various disparate systems to have a single view of the data. Enterprise dashboards need to be able to communicate with multiple business applications in order to display the correct information and apply correct rules in order to display certain data. This calls for a solution that offers a low cost, open standards-based option for executive decision making. Web services are an effective technology to power EDDs. Since Web services are loosely coupled and interoperable, it is easy to expose and extract appropriate data from enterprise systems. The EDD would consume these Web services and processes the data to derive the appropriate metrics, which are then displayed. This could be similar to a portal screen with a high degree of personalization depending upon the type of metrics chosen by the decision maker. This results in shorter lead-time for decision making by making available timely information across the supply chain, by accessing data from multiple sources, and bringing in a high degree of interactivity with the information using drill-down features. Let's examine the applicability of Web services as a solution in the context of a specific industry vertical.

EDD in the Context of the Automotive Industry
We will discuss a Web services-based EDD architecture in the context of the automotive industry. The automotive industry is characterized by global economic slowdown, global overcapacity, decreasing prices and margins, consolidation, etc. Large automotive companies operate across geographies, a phenomena that can be partly attributed to consolidation among car companies, suppliers etc., which has resulted in fewer, larger companies that have more complete product lines. Moreover, consolidation in the automotive industry has resulted in the automotive companies having to deal with disparate systems spread across geographies and supporting differing business models. The automotive companies have large, complex information technology investments. The disparate IT systems in place within the automotive company bring in problems related to information access and decision making. Seamless information sharing across the global operations of the automotive company is necessary to leverage the benefits of consolidation such as cost reduction and effective information access. Appropriate alignment between geographically dispersed business units and functional groups is required to create a unified view of sales, dealers, consumers, products, and services. Currently, each business unit, functional group, and brand operates through independent systems, programs etc. As a result, there is limited synergy across the organization, leading to inefficiencies and lack of coordination. In the following section we illustrate a typical decision-making scenario in an automotive company and explain how the problem can be addressed through Web services-based EDD.

About Sriram Anand
Dr. Sriram Anand is a principal researcher at Infosys Technologies, Bangalore. Prior to joining Infosys he worked in IT consulting as well as product engineering in the US for over 12 years. His interests include enterprise architecture, service-oriented architecture, and legacy integration and software engineering methodologies. Dr. Anand is experienced in designing enterprise architectural strategy for leading U.S. companies in the financial services, retail, and pharmaceutical domains. He holds a Bachelor?s degree from IIT-Madras with a PhD from SUNY-Buffalo, USA.

About Dr. Jai Ganesh
Dr. Jai Ganesh is a Research Associate with the technology research division of Infosys Technologies Limited. He obtained his PhD in information systems from the Indian Institute of Management Bangalore (IIMB) in 2003 and holds an MBA degree in corporate strategy and marketing. His research focuses on Web services, IT strategy and adaptive enterprises.

His research has been published in journals such as Information and Management, Journal of Global Information Management, International Journal of Retail and Distribution Management, etc. and conferences such as AMCIS, ICWS, ICEC, ICEB etc. He serves as a reviewer for a number of peer-reviewed journals and conferences, and has consulted for many software firms.

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