Today, embracing the digital revolution is key to enterprise growth. But, with digitization comes the worries related to managing unstructured data.
Given that we live in a world where communication channels are proliferating at break-neck speed, it’s only natural that large amounts of data accrue from these channels - think IoT, social media platforms, online marketplaces, search engine queries, device data, live streaming services and more. The constant inflow of disparate data is making it increasingly harder for enterprises to map and store this information within pre-configured databases.
What Is Unstructured Data?
When data lacks a defined organizational model or cannot be easily placed into a data model, it falls into the category of unstructured data. Lacking a specific format or organizational schema, unstructured data can be in text form (character strings) or non-textual (media, audio, imaging) form. The lack of structure within these types of data makes it difficult to classify and deploy within an organized computing or storage framework such as a relational database.
It’s important to understand that unstructured data is not a new phenomenon. In fact, just a couple of years back, Gartner had estimated that over 80% of enterprise data is unstructured.
Where Do MDM Systems Fit In?
The prevalence of unstructured data represents both a rising opportunity cost and a security risk for many enterprises. That said, a powerful master data management (MDM) solution can be deployed to tap into the potential value and offset the challenges represented by unstructured data.
Traditionally, the conversation around master data management has revolved around different data governance models and information support for business operations. But in today’s scenario, where data is being generated at an exponential pace (90% of the world’s total data was created in the past 2 years), MDM platforms can offer help in managing and adding context to an endlessly growing stream of data from multiple channels, and in diverse formats. Here’s why:
1. Better Data Quality:
The issues of quality affecting unstructured data are usually due to both machines and people being unable to usefully process, analyze and store the information. MDM systems are designed to clean and organize unstructured data while aligning them toward the needs of multiple stakeholders within and outside the enterprise. This means that the same data can be accessed by a machine system and a human resource in the configuration that is best suited to each.
2. Integration with Enterprise Data:
Today, enterprise data integration is primarily done via APIs. This makes it easier for MDM systems to parse unstructured MDM data smartly in various ways like semantic and sentiment analysis procedures to identify and structure data by assigning taxonomy and metadata to each file. Once data structures have been identified, a powerful MDM platform will be able to link and match information with your master data files, essentially integrating it into your enterprise systems.
3. Data Search and Accessibility:
Many business users would like to be able to access data from multiple channels via an intuitive search interface. However, enterprise search algorithms often cannot parse unstructured data, and this leads to poor search results for users. MDM systems use APIs to index files across the enterprise and build an integrated, system-agnostic search capability, using a mix of cross-referencing to source and metadata tagging to search for and link multiple data formats, whether structured or otherwise.
4. More Accurate Customer Targeting:
The deluge of unstructured information streaming in from various customer touchpoints offers a new paradigm for customer relationship management and lead nurturing. By assessing customer preferences, shopping behavior, and segmenting your target markets, you’ll be able to build personalized experiences and target the right buyers with the right products at the right time. But all these initiatives require reliable customer data. An MDM system tackles your customer data management challenges, by cleaning, enhancing, and connecting your customer information streams, helping your organization make smarter decisions, faster.
5. Enhanced Data Security:
The first step to securing your data is knowing where it’s stored. Siloed data systems represent a security challenge for almost every enterprise, especially when the data from each silo falls under disparate governance protocols. MDM platforms help you get rid of duplications and allows you to manage all your data from one central repository. Furthermore, when implemented correctly, MDM facilitates enterprise-wide security practices including user authentication and authorization, targeted file encryption, access logs and reporting, and security alerts for deviations from existing processes and access parameters.
In conclusion
As an information management tool, whether dealing with low-volume information feeds or with the endless influx of big data, MDM systems often deliver unparalleled value. Not only do they help you organize and track unstructured data, but they also help keep your data footprint secure. When paired with a powerful analytics engine, an MDM can be a goldmine of insights, helping you discover new relationships, hierarchies and customer sentiments, to access fresh markets.
And besides all the above, these systems also help democratize and structure data access within your enterprise, helping your teams quickly access the information they need to create new business initiatives and innovations.
Pimcore’s master data management (MDM) platform lets you meet the right data quality standards for various datasets, be it structured/unstructured or internal/external. It can manage as well as maintain separate versions of your structured and unstructured data in a single place, significantly boosting your data governance and data stewardship.
Also, by connecting all kinds of data, Pimcore ensures a round the clock availability of master data.
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