Trusted Data On Time, Every Time- With MECBot’s Master Data Management

According to the definition by Gartner, Master Data Management, or MDM, is a technology-enabled discipline in which business and IT work together to ensure uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets.

Simply put, Master Data covers those elements of your business which are the most valuable and important for its functioning. Customers, products and locations are all master data domains. 89% of executives agree that inaccurate data impedes their ability to provide consistent customer satisfaction. Further, without proper governance of data, there is limited accountability and scattered ownership of data, which creates compliance risks as well as higher expenses and lost revenue.

This is why MDM is being increasingly adopted in business practices. In fact, according to a survey undertaken by Forrester Research, 47% of 274 professionals said that the scope of their MDM programs includes more than two data domains to master.

Challenges in Implementing Master Data Management

Several challenges are thrown up at your data team during implementation of MDM, such as inconsistencies in the data value chain (the process of collection, publication, uptake and impact of data), inconsistent data formats, and the sheer lack of inter-domain and intra-domain relationships in traditional databases. Lack of data and process governance is another thorn in the side of businesses implementing MDM, which could also lead to a loss of important details during faulty or incomplete versioning of data. Consuming data from different sources may also lead to duplicates or inconsistent values that need to be validated and de-duplicated. For example, in the case of a bank, its different branches would each have an on-premise, detailed database of its past, present and future customers. Then, there would be a centralized customer management platform like a cloud-based CRM, for instance, which will have a consolidated view of customers across all branches.

Apart from these databases, each team of the bank will have a different view of the customer. The customer support team will have a clear picture of the problems and challenges faced by customers, mostly in the form of unstructured and semi-structured data, while the business development teams and the sales teams will have databases around leads pipeline and unstructured data around customer needs. The marketing team will have in-depth records around responses of diverse customer segments to specific campaigns as well as customer lifetime value, profitable customer segments, and loyalty scoring. The product team will be able to link the customer behavior to the product performance, and finally, the finance team will have a grip on metrics like cost-to-serve each customer, ROI, revenue per customer, and so on. Further, third party platforms like CRISIL will have critical information around the customers’ creditworthiness. Online sources will have extensive data on the customers’ reviews and feedback, while banking industry reports will contain rich macro data around consumer behavior trends and customer expectations.

Each of these fragmented views are critical to decision-making of the bank, but when left in silos and in the absence of sound master data management, inconsistencies creep in - leading to severe dilution in the worth of the data and crippling time lags in the insight generation process.

Master Data Management Using MECBot - An Integrated Approach

In MECBot, Master Data Management is an ingrained capability that is a part and parcel of all data operations, processes and insight generation. MECBot’s MDM entails setting data stewardship rules, standardizing data, and cleansing all data of noise. It is focused on key business aspects such as customers, suppliers, products, services, and employees. Strong MDM governance leads to greater consistency of data, cuts costs, and improves the accuracy of data. This, in turn, helps drive up consumer satisfaction, as well as helps expand operations globally. MECBot, therefore, leverages MDM to help your business to use its data competitively.

In particular, the following two aspects of MECBot make MDM a natural and effortless outcome for our users.

Entity Domain Model (EDM)

MECBot is based on the Entity Domain Model or EDM, which makes the platform highly agile, comprehensive and powerful. The Entity Domain Model has two key components - Entity and Domain. Domain refers to a business area that you are dealing with -  like Banking, Insurance or Retail. MECBot starts by defining the ‘attributes’ for your business. A logical group of attributes then form an ‘entity’, and a group of entities constitute a ‘domain’. Each value assigned to an attribute of an entity of a domain at a given point of time is called a ‘fact’ about the entity. A user can create the entity domain model for any domain by identifying and mapping the relationships between various entities and their attributes and ingesting data in MECBot to provide inputs to the model.

The EDM is at the heart of MECBot. It sets forth universal rules of consistency and unleashes identifiers that can consistently correct irregularities in your data from both external and internal sources, thereby becoming a direct enabler of MDM. It works to unify information across multiple channels. It also provides and maintains a single view of your existing data, while at the same time creating a master catalogue of new incoming data, regardless of whether the data is structured or unstructured.

Circling back to the example of a bank that we considered in the introduction, MECBot’s EDM and master data management unifies, cleans and removes the inconsistencies in the diverse and fragmented views of the bank’s customers that remain at the disposal of its different teams and external stakeholders. This single, unified, customer view can now be sliced and diced by decision makers of the bank for smart data discovery, automatic pattern recognition and data-driven decision-making.

Knowledge Graph

MECBot overcomes the key challenges of traditional databases by deploying Knowledge Graphs, and making the entire unified analytics solution affordable to all enterprises anytime, anywhere for collaborative big data analytics within the enterprise team. It preserves its lineage through versioning, maps relationships and ontologies and refreshes these data and relationships in real-time by updating the graph.

In a Knowledge Graph, data takes the back-seat, while relationships between the data arefirst-class citizens.” Therefore, value generation in a Knowledge Graph happens by linking data-points in the form of a graph to generate coherent insights. Entities, attributes and the underlying base of their relationship can be better captured in the form of a graph due to its inherent structure of vertices and edges. In MECBot, these tools are embedded into an automated functionality that underlies the data ingestion process and converts all ingested data instantly into linked-data format with just a few clicks by the user.

When data is organised and seamlessly linked to each other with the primary focus on context and relationships, it also increases trust in your data, especially when you can view an integrated set of products, customers, suppliers, materials, and so on in a single, unified view. Knowledge Graph helps you to expand your database by allowing you to combine data from different sources under one view, while at the same time making your data more accountable. For example, a domain can have multiple entities and each entity can have multiple attributes. Further two or more entities may have several identical attributes. The identical attributes themselves might end up having different names and/or data types. These inconsistencies and overlaps lead to duplications and redundancies in the data. MECBot takes an attribute-first approach. In the above scenario, for example, MECBot defines a unique identifier (say ‘id’, for example, with data type ‘string’) only once. It can then be re-used to uniquely identify all entities like User, Product, Transaction, Market, Brand, etc. Each entity has its own unique identifier as defined by the 'id' field. Thus, MECBot ensures a clean, coherent and well-defined master data by design and does so right from the beginning.

At the end of the day, it is all about keeping your master data clean and ensuring impeccable data governance, which is exactly what MECBot’s Knowledge Graph helps you with. By keeping your master data noise-free and consistent, it provides you with the ability to analyse data and reflect on your business to adapt to the ever-dynamic market conditions and drive your revenues up.

Let us explore these benefits with the help of a few brief use cases.

Use Case 1: Customer 360o

Having a Customer 360o view simply means that you are viewing your customers holistically, from all angles. Therefore, your data is derived from all types of customer touchpoints –– the past, the present, and the future. The past includes things such as product or service activity, recent product views, and so on. Present data covers things such as the customer’s profile, and how they fit in with your business views. Using past and present data, you can construct assumptions of future data which will help you make a personalized plan for each customer –– which in turn can increase sales by up to 20%.

Since Customer 360o entails a lot of data from a large number of sources, it is important to implement MDM while attempting to understand your customer base. Customer MDM allows you to get to know your customer better by linking all your data across different systems and different databases together. This gives you a consolidated, singular view of all the scattered customer data, and in turn, helps you to make business decisions more effectively. Customer MDM can help drive up customer satisfaction by increasing customer service quality, and jump up your sales by increasing the quality of your marketing & promotional campaigns. It also helps you to target your customer segments and even micro-segments better, depending on their behaviour patterns which are auto-detected and feed into personalization of marketing.

Use Case 2: Optimizing Channel Marketing For Retail Brands

Channel Marketing aims to distribute products through different channels which are set up to optimize the number of customers that are reached through these various channels. Retail brands sell their products through different types of channels, such as retail stores which include departmental stores and specialty stores, online and catalogue retailing, distributorship and stockist-based channels, and more.

Using MECBot, Retail MDM could help foster omnichannel marketing for retail brands, which in turn, would help increase customer base, improve customer satisfaction and augment brand loyalty. MDM also helps in providing a personalized experience for all customers, by providing a unified view of channel data that is easy to analyse. According to a study, 88% of retailers claim that personalization has increased the effectiveness of their marketing. Furthermore, MDM ensures error-free, ownership-driven, trustworthy data, which provides a seamless experience for end-customers as well as retailers. Not only does MDM help with personalization, but also with keeping track of product data, which can help retailers make the most of the key success factors in their sales and detect underlying patterns when sales are lower or higher in certain markets, geographies, seasons, and so on.

Use Case 3: Compliance Risk Management

Compliance risk management is an important function of most businesses, who have to ensure that their business functions fall within standard regulations and norms. Non-compliance attracts fines, penalty and tarnished reputation, and could lead to bad publicity and loss of business.

MDM in MECBot can be used to manage compliance risks as well. Companies can use historical data of non-compliance to build a database of commonalities, which can then be analysed to come up with ways of ensuring that regulations are being complied with. It is also important to stick to regulations about customer practices, which can be done by analysing customer data and identifying key areas where there are drawbacks. For example, MDM is helpful while dealing with mandates such as Know Your Customer (KYC), which requires a large amount of data to be collected. Data governance is an important part of regulation compliance, which can also be tackled by using MDM within a controlled governance framework.

About MECBot: The #1 Augmented Data Management Platform for Real-Time Analytics at Scale

MECBot puts your business first by adopting the Entity Domain Model approach, which operates without any dependency on the underlying databases or the structure of the data. It comes bundled with a self-service, intuitive interface and takes care of all your data management and analytics requirements in a centralized manner, including scalable deployment.

Simply put, MECBot automates the entire data unification process envisaging all forms of data at scale, and delivers unprecedented business results. To accomplish this, MECBot first structures the unstructured data contextually using domain-specific business ontologies and marries it with structured transactional data in near real-time. This creates a comprehensive Smart Data Graph for an enterprise (Smart Enterprise Knowledge Graph).

This Smart Enterprise Knowledge Graph is accessible through “Free Form Vertical Search”, APIs, SparkSQL and Graph QL. MECBot’s unique value propositions include:

  • Simplicity: Sets up the application with just a few clicks. Gives results from day 1.
  • Speed: Matches the pace of decision-making with the speed of the original data generation.
  • Scale: Performs elastic scaling based on business needs with dynamic clustering.
  • Security: Offers banking grade security and role-specific access to the platform.

MECBot saves more than 80% of pre-processing time & cost and delivers highly actionable insights to boost your ROI manifold. It is the only platform that puts your business first, not data. Its unique, built-in capabilities drastically reduce the burden on IT infrastructure and empower your decisions with powerful business intelligence in real-time through augmented data management.

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