Data Management Solutions
Data Management
Data management (DM) is the set of related disciplines that aims to manage the data asset fully, from conception to archiving. While data management and data integrity protocols are composed of the numerous data initiatives within the organization.
Efforts invested in strengthening quality are critical to ensuring decisions are made based on accurate, timely, and relevant data. The associated work of maintaining high-quality data through appropriate data governance magnifies the return on investment by embedding the importance of data as a strategic asset into the fabric of the organization’s structures and processes.
Data Strategy
Most businesses gather data from a number of different systems and channels. Integrating that data and knowing what to do with it, can often be time consuming and complex.
Would your business benefit from having access to all of its data from one single point? Doing so would allow you to understand your customers to drive more revenue, find out where the bottlenecks are in your operations and reduce costs, or improve your marketing ROI.
If you are currently working on or thinking of progressing your data strategy and don’t know where to begin, Nandini Consulting can help cut through the complexities, and craft a data strategy that won’t gather dust on the shelf, but can be deployed to deliver immediate business value.
Data Governance and Data Quality
Data governance is the overarching policies and processes that govern the management of company data. The purpose of data governance organization within the company is to identify what information is important, establish the processes to manage it and measure the effectiveness of the effort in achieving business objectives.
It helps to manage and resolve data related issues, and understand and promote the value of data assets. As part of the initiative we help you define policies, standards, procedures, and metrics in order to get consistent and reliable data throughout your organization. Track, and oversee the delivery of data management projects and services.
Enterprise Data Architecture
Data architecture describes how data is collected, stored, transformed, distributed and consumed. IT includes rules governing structured formats, the systems for connecting data with the business process that consume. Typically, it provides models, policies, rules, or standards that govern which data is collected, and how it is stored, arranged and put to use in a database system and or in an organisation model of information about different systems in the organisation (Trading, Risk, Reference Data, CRM, etc.).
Approach We Take To Data Architecture
The Approach Our Data Architects Follow Is Split Into Four Distinct Areas
- Current Architecture Assessment
- Future State Logical Architecture
- Future State Physical Architecture
- Implementation Roadmap
Frequently Asked Questions
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