What is Master Data Management:
With the ever-evolving business dynamics, organizations aspire to quickly turn data into insights to stay ahead of the change. An agile and mature master data management (MDM) software that acts as the single source of truth with defined role and ownership plays a critical role to help organizations address change and stay ahead of the competition. The confluence of people, process, and technology in MDM creates an operating model and intelligent master data framework which eliminates silos. Most leading organizations have embarked on a journey to optimize and streamline their master data operations to gain competitive edge.
Master data process involves collecting, recording, and storing data in various source systems, objectively understood as data input. This is followed by:
- Integrating source systems to extract the data into a data lake
- Clean and transform the data into a trusted quality data
- Load to data warehouse for downstream consumption
The output of an efficient MDM process is critical and trusted data of highest quality, that is leveraged for accurate and actionable business insights.
Let it Happen or Make it Happen!
While the paradigm shift towards managing master data is a known sphere, there are still traces of conventional master data management practices which exist.
Let it Happen Strategy: The ‘Let it happen’ strategy is the unaware or reactive stage i.e., bottom level in the MDM maturity stage. An enterprise can only identify duplicates through conventional excel methods and can, only to some degree, remediate it. This highlights little expertise to resolve issues cropping up from duplicate and incorrect data. A fair inference is that it highlights an organization’s inability to manage data quality.
Make it Happen Strategy: The true potential of master data is unearthed by devising a master data management strategy basis
- WHY - Mission MDM
- WHAT - Focus areas (Goals and KPIs)
- WHO - People (Data Stakeholders, Data Stewards)
- WHERE - Business processes
- HOW - Data quality rules and definitions
This covers end-to-end master data governance strategy, that is aimed to use enterprise master data in it’s true sense. A ‘make it happen’ approach, therefore involves enforcing MDM governance that improves data quality, de-duplicates, enrich the existing data to make it more meaningful.
Master Data Management Applications:
Organizations aiming to drive true business values are looking to deploy MDM applications that help them align with their data quality strategies. The new crop of MDM tools is pushing the boundaries of MDM 3.0. Hence it is critical to select a progressive, future proof, value driven MDM tool to ensure success of an organization’s data strategy. From the many tools available, here are a select few and how they transform an organization’s data strategy, enabling business agility through a single source of truth from trusted, organized, and governed master data.
Currently there are various players in the market who offer their software (software-as-a-service) or platform (platform-as-a-service) to help organizations realize true potential of data residing in silos within various functional areas. These master data management solution providers focus on all aspects of MDM process and hence it is critical to evaluate them from both offering and cost perspective. A right tool at right cost with right solution is the key before finally selecting one.
Here is a list of few eminent players with proven expertise:
Informatica: A veteran, and market leader in MDM space, has several products that can either be deployed on-prem or on cloud. Core features include data acquisition, enrichment, de-duplication, integration, quality, and governance. It further helps in identifying relationships within data, transactional & social data integration to process actionable insights. It is a proven performer with scalable solutions.
Riversand: With its variety of designed solutions, Riversand through its multi-domain MDM and cloud native platform helps organizations do data governance, data quality, dashboarding, insights, etc. Strength of this tool lies in providing support to multiple domain MDM (multiple MDM tools) along with multi-domain MDM (single tool supporting multiple). The tool has built-in capabilities for data governance and data quality.
Tibco Software: Tibco has robust data governance, and manages master data, including reference data, hierarchy, and taxonomy. With its flexible data modeling, collaborative workflows, and real-time integration options, it provides organizations with strong visualization and workflow capabilities.
Ataccama: A platform with proven solutions for data profiling, data governance, data quality and master data management, it supports multiple domain MDM. It thrives on its core-features such as data consolidation, business rule enforcement, data monitoring & editing, data authoring and auditing, and analytical MDM. It supports big data integration and with its proven capabilities, it provides scalable solutions.
Profisee: A fast, scalable, and affordable solutions delivering trusted data across the enterprise. Profisee MDM provides first of its kind cloud-native containerized platform-as-a-service (PaaS). It helps customers to choose their preferred choice of deployment - on-premises or on-cloud, as well as a hybrid model. With golden record management as its one of the core features, Profisee brings in data modeling, stewardship, governance, and enterprise workflows. Profisee stands out as a multi-domain MDM within a single environment.
Reltio: Offering a scalable solution to meet the needs of both smaller organizations and big enterprises, Reltio supports both structured and unstructured data. It allows for collaborative data stewardship, rating, and segmentation. Delivering highly robust compliance capabilities with field-level audit history. Big data insights and recommended actions are some of its core features along with data-as-a-service capabilities for access to third party data sets.
Adopting the Right Master Data Management Software to Suit Your Data Strategy
With rapidly growing enterprise data, MDM tools are gaining importance. While data volumes are growing with emerging technologies, the obsolescence is phased. This calls for organizations to manage and prioritize data which would include integrating different source systems and then remediating them into clean and trusted data for actionable insights.
Each MDM solution has its own strength and weakness. Once the organization has created their data strategy, they need to choose the right fit MDM tool/software to ensure the success of their data strategy. Most organizations would collaborate with consultants to help them chose the right MDM tool for their requirements. A wrong MDM tool can not only fail the data strategy but would also cost the organization dearly. Consultants can study the maturity of data needs within an organization and assist them in building the right business case for MDM adoption. A right tool can only perform as per its design and program, but it is more important to build an enterprise-wide culture to adopt MDM across all levels and departments.
About the Author:
Business Consultant, Capabilities – Retail, e-Commerce and Consumer Business, Tech Mahindra Business Process Services.
Nitin holds a Master of Business Administration degree specialized in retail and marketing and comes with 13+ years of experience. He has managed MDM transitions and operations for multiple clients within different geographies. With Six-sigma green belt certification and proven expertise over the years in Business process management, he has led various automation and transformation projects.
Please reach out to him @ Nitin.Anubhaw@techmahindra.com