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November 8, 2019

Organizations are rushing to tap the value of their data to sustain themselves and gain an edge in a hyper-competitive ecosystem. This has triggered a need for enterprises to access relevant data with agility. Traditionally, this has depended on enterprise IT making the required data available in the required format.

While IT might be able to meet the data management and reporting needs of enterprises, the efficiency of this model is increasingly being questioned. Business and IT teams often work in a segregated fashion, causing IT to not have complete insight into the precise nature of data requirement of business. This inevitably increases IT’s time of delivery of appropriate data. Also, even for IT, lack of automation in basic and recurring data management tasks translates into operational inefficiencies and error-prone outcomes.

The Self-Service Option

Enterprises are looking for automated and tool-based data preparation, reporting and management, which business team can potentially handle directly. Sensing this shift in approach, data management software vendors have started to redesign their software, to make them directly operable by individuals without technology skillsets. This is the essence of “self-service” data management—enterprises servicing their own data needs. At a more elevated level, self-service is about any intended user of software (Business/IT) being able to use it with minimal support and high efficiency. In some sense, B2B software is emulating B2C software, which is inherently of self-service nature.

Key Features of Self-Service Data Management Software

A self-service data management software may be expected to exhibit the following five basic traits:

  • Friendly User Interface: A user’s way of interacting with a software, and the resulting experience (good or otherwise), is quite personal, and hence subjective. Nevertheless, there are a few generally known characteristics of a poorly designed user interface (UI). These include need for excessive clicks and scrolling to accomplish a task; lack of continuity in executing sequential operations resulting in ‘jumps’ from one part of UI to another; and bad placement of web controls making it difficult for the user to decide where to start and what to do next.

A new-age self-service data management software must not only avoid these basic pitfalls but also have an overall simple-in-design and easy-to-navigate UI. To take it to the next level, the UI must be dynamic and tailored for the persona of the user accessing the software. This way, users (business or IT) see only what is required for their functions and roles. For example, a business user sees frequently required reports, charts and dashboard on the home page; an IT user sees status of data processing jobs and alerts; and an administrative user sees user management, grant of entitlements, access to audit logs etc.

  •  Bi-directionally Interactive Software: New-age data management software should actively provide users, recommendations and guidance related to operations. Powered by ML/AI, the software can issue alerts and reminders, and notifications about pending and completed processes as well as guidance during process failure. This is a marked departure from the approach of older data management software, in which inputs/instructions are essentially conveyed by the user to the software. In other words, new data management software elevates the style of functioning from ‘do-as-directed’ to ‘direct-for-doing-the-right way’.
  •  Intelligent Support: Self-service does not imply no support. It is imperative that self-service data management software provides sound operational support to the users, who would be using the software on their own. Helpful features include friendly and upfront validation messages when users enter data in forms, upfront alerts about potential exception scenarios, and notifications as well as workarounds/options when exceptions materialize. The software can also have a bot to provide immediate assistance to a user. Furthermore, a self-service data management software should be collaborative, so that software users can reach out to each other for assistance. 
  • Operational Assurance: While executing operations in a data management software, it is important that a user, despite minimal support, be confident about the correctness of procedures and outcomes. Self-service data management software must provide reporting, visualization, metrics and trending features for assurance of correctness of usage. In addition, the software must provide workflow mechanism so that the crucial steps of a data management function are vetted and approved by designated authority.
  •  In-built Security Features: The software must enable “tamper-aware” operations and allow role-based access to the wealth of data that it has accumulated internally for its own functioning. User actions must get logged in the product. Key stakeholders and owners must get notified about crucial operations executed by any user.


Solution for the Future

The notion of self-service data management is here to stay. Sensing growing demand, ‘data management software’ vendors are re-molding their software to make those amenable to quick utilization.


Ashim Roy is the Global Product Head of TCS MasterCraftTM DataPlus, which is an integrated data management software from TCS.  Ashim carries more than 26 years of industry experience in business verticals such as Manufacturing, Investment Banking and IT industry. Ashim pursues his interest in enterprise product development, particularly, in the area of Data Privacy and Data Quality and has 10+ patents under his name. Ashim holds a Master's degree in Robotics from IIT, Kanpur.

Sumeet Bhide handles the Marketing and Branding, and Learning and Development for TCS MasterCraftTM DataPlus, which is a data management software from TCS.  Sumeet has 18 years of experience in TCS and has delivered crucial IT projects in Banking, Wealth Management and Telecom areas. His current areas of interest include Data Privacy and Data Management. 


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