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DATA FABRIC

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MD2 has extensive experience in projects of bases integration of several domains as customers and products, culminating in a unique data platform (master data management) and projects of data integration/analysis in corporations of great expression in the national and international market. We hold a considerable portfolio of projects successfully delivered in this segment and the recognition of our clients and the manufacturer IBM puts us in a prominent position in the Brazilian IT market.

 

MDM has a deep context of data reengineering, involving requirements such as wide connectivity with various data sources, high performance using massive parallel processing for treatment of tens of millions of records), multilayer data model to ensure complete governance in all stages of processing involving the collection of data, the critical processes and data sanitation to apply the routines of quality treatment and retention for curation and especially the mature identity resolution mechanisms to promote the unification of records at the corporate level in a secure and reliable way, maintaining traceability with their respective origins. 

 

An MDM solution requires sophisticated and mature people registry correlation algorithms, which take relevant investments to structure (based on the experience of implementing these algorithms for different industry segments and involving a range of people profiles treated for generating this data hub) and that need to be in constant evolution.

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Master Data is the sensitive information shared in various business processes. It is what provides the context for the company's day-to-day transactions and operations, typically information about people (customers, suppliers, prospects, employees, collaborators), products, and services.

Large organizations have in their operation several systems usually specialized in specific functions that promote the entry and maintenance of registers of people (customers, prospects, patients, partners, suppliers) and things (products and services). These registries conceived for specific functions end up diluting the vision of these information assets, limiting or hindering a corporate vision of this information. This situation generates rework, limits effective communication with people and the identification of products and services.

Simple questions like "how many customers do we have?" receive different answers, because Marketing has one vision, Operations another vision, and Sales another vision. Creating a unified view of people, products and services leverages several new business opportunities, since the potential of a centralized master data base can support several business initiatives: customer experience, CRM, Marketing, communication, etc.

This data is stored in data silos. Their registry vices and data quality are most of the time totally unknown, even by the people responsible for each of these systems. The lack of correlation between these records limits the holistic view.

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As a way to address the problems caused by this systemic gap, companies look to the implementation of an MDM project as the best alternative to complement their architecture with a solution specialized in managing this type of information. This type of platform performs the entire cycle of capture, qualification, and consolidation of this information in a single place. The data recorded in this database goes through a series of critiques and validations that allow only the data with enough quality to support the company's decision-making processes to be stamped so that its publication to the other corporate systems is authorized.

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The data that do not meet these minimum criteria are dammed and alerts are generated so that a team specialized in curating them can evaluate and remedy the problems found.

MD2 Solution and Value Proposition

The solution proposed by MD2 involves the implementation of a corporate architecture for data integration and processing.

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Some of the main characteristics of the solution:

 

Automates the data collection process from the systems that generate and update the registrations, ensuring that all registration changes made throughout the company's operation are captured;

Automates the process of treatment and enrichment of the generated entries considering robust rules of data sanitation and use of external bases of enrichment: DNE of the Post Office, for example;

It creates a more comprehensive corporate base using the MDM methodology (HUB MDM) that will control the collection and treatment, creating the views and scores for the qualification of the records, allowing for better data governance;

Provides sophisticated identity resolution mechanisms, handling duplicate records, controlling the validity of updates and flexible unification policies/rules;

Automates the process of updating and feedback data in Legacy Systems, creating data reliability for the various purposes of the operation;
 

Differentials of the MD2 solution

Diferenciais da solução MD2

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Methodology

Robust single-vision people project implementations with phases and deliverables organized in deployment waves;
Provides the essential phases and activities for a successful data re-engineering project already successfully implemented in large implementations;
100% adherent to the data governance model proposed by the DAMA institute.


Solution Architecture

Solution based on the IBM Information Server Platform;
Adherent to the informational architecture standards in the world market standards;
Foresees intense use of ETL processes and APIs for sharing data and thus causing less impact on existing systems.

 

Playbooks

Robust and consistent data model for establishing the single customer view;
Comprehensive and effective quality rules for handling "People" data considering: discovery, analysis, processing, enrichment, matching and unification;
Customer data management application, with standards, rules, workflow and data curation;
Analytical dashboard for management indicators, traceability and auditing of the repository (hub);
Exposure of data quality services for consumption and exposure of unified and enriched data.

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