Understanding Enterprise Data Governance: Part 2

This is the second blog post in a series exploring Enterprise Data Governance.  In the first post, we briefly defined transaction data, metadata, master data, reference data, and dimensional data.  That discussion primarily focused on transactional data and metadata, and can be found here. In this post, we will further explore reference data and its role in data governance solutions.

As we move beyond transaction data and metadata, and into the realms of master and reference data, most academics and analysts tend to focus on solutions and methodologies rather than attempting to clearly differentiate between the types of data that need to be governed.  Not only does this introduce a solution bias, but it also leads to a tendency to lump these data categories together in master/slave relationships and leave it at that.  For example, reference data is commonly classified as a subset of master data, and dimensional data as a subset of reference data.

Technically, there is nothing inaccurate about these assertions, but it would be a mistake to think that a single solution can fully address all of them without first gaining an understanding of the different challenges involved in governing these various types of data.  Only then can we accurately assess the solutions and technologies that are best suited to the task.  For this purpose, we will treat master data, reference data, and dimensional data as separate, distinct categories from a governance perspective.

Reference data is the easiest of the three types to understand.  It is made up of various lists and code sets that are used to classify and organize data.  Country codes, industry codes, status codes, account types, and employee types are among the many examples of reference data.  Reference data sets can vary wildly in size and complexity.  For example, there might only be a dozen or so valid account status codes, whereas there may be over a thousand valid industry codes.  Code sets related to product SKUs, financial instruments, and the like can be much larger, ranging into the hundreds of thousands or even millions of records in rare cases.

While the concept of reference data is easy to grasp, there can also be significant complexities that need to be addressed.  Some reference data sets are standardized by regulatory, or governing bodies, such as the International Standards Organization, which maintains standardized lists of country codes among other things.

Another example is the US Census Bureau, which maintains the North American Industry Classification System (NAICS).  It is common for companies to require internally managed alternate code sets as well.  For example, an COTS solution may include US territories in an internal State table, requiring this alternate list to be cross-referenced to standardized state and territory code sets for regulatory purposes.

Other reference data sets need to be controlled directly by the enterprise since they relate to how business is conducted.  Sales territories, lines of business, and departments are common examples.  As mentioned previously with the State table example, this can also include the configurations of code sets within applications, such as employee types and account status, when custom business processes need to be accommodated.

From a governance perspective, mastering reference data goes beyond maintaining traditional lookup tables.  The ability to maintain well-documented business and technical definitions of code set values, including data versioning and audit history, are essential.  Functionalities for maintaining and validating mappings between related code sets are also of vital importance.

Keep watch for the third part of this blog series, Understanding Enterprise Data Governance!

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Serene-AST Launches CPQ for Media Demo!

CPQ, media, demoSerene-AST is pleased to introduce its CPQ for the Media industry video demonstration. We’ve developed a revolutionary solution, specific to the media industry, that drives income for companies with a digital presence by leveraging Oracle CX Cloud solutions.

In the video, three separate use cases are demonstrated:

To view the full-length video, please click here. Also under the same account, separate videos for each use case can be found.

Look forward to more videos in the future!

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Serene-AST Celebrates Opening of New Office in India!

As everyone in our global locations celebrated and welcomed the new year, AST’s branch in Pune, India had something extra special to celebrate! On December 22, 2016, the Pune branch opened the doors of a new office location with an official Ribbon Cutting Ceremony.

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Congratulations to everyone involved in opening the new space! We are excited about our continuing growth and expansion, and hope that everyone continues to follow us in this exciting journey.

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Understanding Enterprise Data Governance: An Introduction

From executive sponsorship to the execution of effective, collaborative work flows, human interaction is critical to the success of any data governance (DG) initiative.

Typically, the technical aspects of data governance are much easier to control. Given the enormity of the topic, we will first define the types of data involved and introduce some of the key technologies that can be leveraged.

First, a few simplified definitions:

  • Transaction Data is data that describes an event. It makes up the majority of data found in data stores within applications and data warehouses.
  • Metadata Data provides definitions and descriptive models of various data sources, data elements, and processes.
  • Master Data provides a best version enterprise view (or golden record), linking many references to a business entity (i.e. customers, locations, products, suppliers, etc.)
  • Reference Data includes internally and externally defined classification schemes (codes and types) required by many systems.
  • Dimension Data includes master and alternate hierarchical structures used for financial systems, data stores, reporting, and analytics.
  • Data lineage is defined as a data life cycle that includes the data’s origins and where it moves over time. It describes what happens to data as it goes through diverse processes.

All business applications make heavy use of transaction data. Note that transaction data conforms to metadata and can include all the other types of data. For example, you will find elements from all of the data categories listed about with the Oracle Enterprise Resource Planning (ERP).

Metadata describes how data is formatted and organized, how it is used, and can also include allowed values. It does not include the actual data values that relate to specific business events. All transaction data elements will typically correspond to fields in a database table, which are, in turn, well described by multiple metadata solutions. The Oracle database uses a specific metadata protocol, descriptive language (DDL), to define and create the table.

Broader metadata tools, like Oracle Enterprise Metadata Management (OEMM), can also model processes that interact with the database, such as data transformation flows and business workflows. OEMM also allows the business and technical metadata definitions to be governed via workflows, and supports detailed data lineage analysis.

In our next update, we will explore enterprise data quality, business intelligence, and master, reference, and dimensional data technologies, and their roles in data governance solutions. Future updates will also include data authoring versus data consumption, big data, and the cloud, and their impacts on DG initiatives.

To learn more about utilizing Oracle’s Enterprise Metadata Management and Data Quality products, click here.

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Serene-AST Webinars: Powerful and Packed with Knowledge

On September 1, 2016, Serene-AST, LLC hosted an informative webinar, highlighting our solution that enables Salesforce customers to enjoy enterprise-class data management by leveraging Oracle Customer Data Management.

The solution seamlessly integrates Salesforce and Oracle Customer Data Management, allowing the Salesforce CRM system to enable real-time Enterprise Data Management/Data Quality solution. Unifying all data to one system allows organizations to consolidate, validate, and continuously cleanse customer data in order to provide a comprehensive and accurate view to their sales and service teams.

If you missed our SFDC webinar, don’t worry! We’re hosting another free and informative webinar at a later date. This time, we’re discussing challenges in the High Tech and Semiconductor industries, and how the Serene solution, built on Oracle CX Cloud, can improve processes, revenue, and overall best practices for your organization. This solution helps organizations truly understand their sales pipeline and forecast via complete information gathered from CRM systems.

We look forward to your attendance, and sharing our knowledge of this incredible solution with you.

2016 Customer Experience Trends, Evaluated

At the start of the year, Forbes put together a list of the most visible trends relating to CX. Now that we’re halfway through 2016, we can analyze these trends to see what was accurate, what was not, and what we can expect for the second half of 2016.

While all of the points made by Shep Hyken, the article’s author, are accurate, here at AST, we see mobile, omni-channel experiences as the top CX drivers.  Customers look to deliver customer service through mobile devices using geolocation, push notifications, SMS, social media, and mobile-friendly features.  Conversely, drivers such as YouTube for service have a reduced impact on CX.  Does your organization see a difference in the predicted trends?

Serene-AST Deploys Oracle Cloud

On June 20, Serene went live with the first phase of an internal Oracle Cloud ERP project, which includes Oracle Cloud Financials, Cloud Project Portfolio Management, Workforce Deployment. “As an Oracle Platinum Partner, we feel it is extremely important to ‘drink our own champagne’,” aid Vinay Saini, CFO of Serene-AST, LLC.

The solution will become the single common platform on which Serene and its parent company, AST Corporation, will operate, and includes functions such as:

  • Time entry and expense reporting
  • Project management and execution
  • Establishment and government of all projects
  • Corporate functions, such as Accounts Payable, Receivables, and General Accounting

Congratulations to our team on achieving this milestone!

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Serene Attains Oracle Cloud Premier Partner Status

Serene Corporation, and its parent company AST Corporation, are pleased to announce their attainment of Oracle Cloud Premier partner status. This recognition is due to the expertise Serene and AST have demonstrated in their multiple, successful Oracle cloud go-lives and their dedicated Oracle cloud-certified resources.

Serene and AST are extremely pleased to have attained a high level of partnership so quickly. We are committed to building upon that success by increasing successful adoption of Oracle cloud solutions world-wide.

Seven Evaluations for Second-Generation MDM Tools

David Loshin provides seven evaluation considerations for selecting MDM solutions in this article.  His portrayal of second-generation MDM tools will surely excite many data management professionals.  Before discussing further, it’s worth mentioning that he definitely got it right in his book, Master Data Management, when he said: “The key to a successful MDM initiative isn’t technology or methods, it’s people: the stakeholders in the organization and their complex ownership of the data that the initiative will affect.”

Indeed!

All too often, Master Data Management (MDM) initiatives are led by IT departments that prioritize architectural and technical considerations above business enablement.  It is well known among seasoned MDM professionals that Data Quality (DQ) initiatives can create significant business impacts without MDM, but MDM initiatives always requires DQ to fully realize their potential.  For this reason, we recommend leading with DQ to deliver business value in conjunction with MDM evaluations. This strategy would provide feedback into the evaluation to help ensure priorities are informed by real-world examples.

The seven characteristics David presents are:

  1. Identity resolution
  2. Physical versus virtual
  3. Master entity modelling options
  4. Synchronization
  5. On-premises versus cloud based
  6. Data management approach
  7. Data governance

The linked article provides a concise introduction to each topic.  While none of these concepts are new, vendors are constantly exploring innovative approaches to delivering MDM software products. Early adopters should evaluate the MDM/DQ business solutions when using next-generation products before deploying them.

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Are You Ready For the Resurgence of Chat Bots?

Chat bots have been in the news lately – not something like “Clippy” from Microsoft, which was universally loathed, but bots capable of providing natural language processing.  These bots can be placed in your customer-facing service center for assistance in different capacities, such as help centers, social media, travel planners, location finders, and more.

The article below explores how some companies, like Facebook and Microsoft, are working on providing these bots to their customers through APIs.  This allows companies to build bot integrations into other CX tools to enhance the value of existing products, effectively adding virtual assistance to any application that can tap into web services. 

Check out the next thing in automation!

http://www.itproportal.com/2016/05/01/talking-chatbots-time-to-enhance-customer-experience/ 

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