Friday Mar 21, 2014

Master Data Management: How to Avoid Big Mistakes in Big Data

Big Data Quality MDM

Master Data Management: How to Avoid Big Mistakes in Big Data

The paradigm-changing potential benefits of big data can't be overstated—but big changes can deliver big risks as well. For example, exploding data volumes naturally create a corresponding increase in data correlations, but as leading experts warn, correlations should not be mistaken for causes.

To avoid drawing the wrong conclusions from big data, organizations first need a way to assemble reliable master data to analyze. Then they need a way to put those conclusions and that data to work operationally, in the systems that govern and facilitate their day-to-day operations.

Master data management (MDM) helps deliver insightful information in context to aid decision-making. It can be used to filter big data, isolating and identifying key entities and shrinking the dataset to a manageable size for parsing, tagging, and associating with operational system records. And it provides the key intersecting point that enables organizations to map big data results to operational systems that are built on relational databases and structured information.

Adopting master data management capabilities helps organizations create consolidated, consistent, and authoritative master data across the enterprise, enabling the distribution of master information to all operational and analytical applications, including those that contain customer, product, supplier, site, and financial information.

Oracle Master Data Management drives results by delivering the ability to cleanse, govern, and manage the quality and lifecycle of master data.

To learn more about the importance of MDM as an underlying technology that facilitates big data initiatives, read an in-depth Oracle C-Central article, "Masters of the Data: CIOs Tune into the Importance of Data Quality, Data Governance, and Master Data Management."

And don't miss the new Oracle MDM resource center. Visit today to download white papers, read customer stories, view videos, and learn more about the full range of features for ensuring data quality and mastering data in the key domains of customer, product, supplier, site and financial data.

Friday Mar 07, 2014

Master Data Management and Big Data: Perfect Together!

By Gino Fortunato

Master Data Management and Big Data: Perfect together!

The 'hot' button around gathering customer insight is Big Data.  And justifiably so.  Using Big Data is a great way to harness previously unusable data to look for patterns in the data crumbs that customers leave behind.  By rapidly processing this data in real time, Big Data allows customer insight that was previously impossible. 

Much of this insight is statistical.  Customers have similar patterns.  They abandon shopping carts when something is out of stock or when they see the final price.  At least compared to other points of the buying process.  It's just human nature.  By using statistical and other techniques, driving insight about what the customer is doing, or might be doing next, can drive a lot of value. 

But wouldn't it be great to use that Big Data insight along with what you already know about that customer?  That's where MDM comes in.  MDM is the spot to operationalize what you already know about the customer.  By using what you already know, plus the insight you have gleaned from Big Data, you can make informed decisions about how to react to the customer's next click.  And do it in real time.   To properly use the insight, it is necessary to properly idenfity the customer.  Again, an area that master data management can help.  With it's built in identity resolution capabilities, MDM can help in two ways.  One is to add to what is being derived based on the Big Data source.  The other is to prevent mistakes when the statistical analysis is wrong.  For example, the customer surfing the gaming site may be grouped into a category that has a number of traits.  One of those traits might be an expected age range.  But if the organization knew the birthdate of the person was outside that age range, they can propose different cross sell/ upsell possiblities and perhaps lead to the discovery of a new subcategory to further open the market.

To learn more about the importance of MDM as an underlying technology that facilitates big data initiatives, read an in-depth Oracle C-Central article, "Masters of the Data: CIOs Tune into the Importance of Data Quality, Data Governance, and Master Data Management."







Tuesday Aug 28, 2012

Master Data Management – A Foundation for Big Data Analysis

While Master Data Management has crossed the proverbial chasm and is on its way to becoming mainstream, businesses are being hammered by a new megatrend called Big Data. Big Data is characterized by massive volumes, its high frequency, the variety of less structured data sources such as email, sensors, smart meters, social networks, and Weblogs, and the need to analyze vast amounts of data to determine value to improve upon management decisions.

Businesses that have embraced MDM to get a single, enriched and unified view of Master data by resolving semantic discrepancies and augmenting the explicit master data information from within the enterprise with implicit data from outside the enterprise like social profiles will have a leg up in embracing Big Data solutions. This is especially true for large and medium-sized businesses in industries like Retail, Communications, Financial Services, etc that would find it very challenging to get comprehensive analytical coverage and derive long-term success without resolving the limitations of the heterogeneous topology that leads to disparate, fragmented and incomplete master data.

For analytical success from Big Data or in other words ROI from Big Data Investments, businesses need to acquire, organize and analyze the deluge of data to make better decisions. There will need to be a coexistence of structured and unstructured data and to maintain a tight link between the two to extract maximum insights. MDM is the catalyst that helps maintain that tight linkage by providing an understanding about the identity, characteristics of Persons, Companies, Products, Suppliers, etc. associated with the Big Data and thereby help accelerate ROI.

In my next post I will discuss about patterns for co-existing Big Data Solutions and MDM.

Feel free to provide comments and thoughts on above as well as Integration or Architectural patterns.  For more information on Oracle Master Data Management click here.

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