Why Automation is Not a Bad Word

by Sass Babayan, CEO and President WynTec LLC

Most consulting vendors in the data management space do not like the word “automation”.  The word implies, ‘less billable time for their consulting practice’.   Within the data management space, these vendors offer consulting resources (on-shore and off-shore) to develop code that requires a rigid process to manage. Not only is this costly, but in most cases it’s time consuming.   These types of vendors employ specialized expertise to perform the complex tasks of managing data and typically have resisted automation.  Why? This resistance is partially driven by their outdated staffing business models, lack of understanding of emerging technologies and lagging behind their competitor’s push to offer more value in automation and delivery based models.    

The emerging vendors who are competitive in the data management space are moving towards metadata driven automation technologies that use outcomes and delivery based pricing models.   These business models are driven by value to the customer so the customer can get their data when they want it, how they want it and where they want it.  To strive for maximum delivery for their customers and achieve a concise delivery model, it is the responsibility of the smart consulting firms to pursue progressive methods of managing their data assets. 

The following questions should be considered closely in managing large data acquisition environments:

• Is it time to move to an outcomes-based business model that leverages metadata-driven automation supported by expert consultants?  Let the automation do the heavy lifting of the mundane and repetitive task of managing the data, while the expert consultants focus their efforts on complex data manipulation.  
• Would your customers appreciate faster delivery, quality enforced and precision processes that generate consistent and quality results?  Let the metadata driven automation tools generate the data loads to obtain quality and quantity.  To keep in step with the increased data appetite that customers have, as seen in the Big Data movement, the marriage of metadata driven automation in the hands of expert resources creates optimum output.
• Will your customer base grow exponentially if your business model was more competitive; actually lowering your cost while delivering more quality, faster deployment, consistent design and measurable output?   

When building a solid data migration and data acquisition strategy in the data management space, the following formula drives a sound outcomes based business model:

Customers are seeking expert vendors that are specialists in the data management practices, who are equipped with the right knowledge and tools to quickly and accurately develop their data assets into meaningful insight.     

The participation of metadata driven automation tools in the data acquisition space can no longer be ignored; embracing these tools in the hands of expert resources achieves the most value to a customer.  Consider the practice of data acquisition, data migration, Data Lake for Big Data initiatives, data extraction and moving data from multiple source systems to a central land and stage environment.  All these technical frameworks and processes share the same requirements of extrapolating heterogeneous data from disparate sources to a target destination.  Typically, you will see this discipline in developing and managing enterprise data warehouses, reporting data stores, analytical data marts, data conversions and data integration platforms.  Within these frameworks, metadata driven automation performs the data management work so the expert resources can focus on complex data manipulation and transformation in order to deliver focused value.  True outcomes are achieved when:

• A metadata driven automation system generates the code to load the data dynamically and in bulk, based on user maintained and user driven knowledge ware.    
• Human instructions are managed via decision trees that are exposed and transparent. Exposing the metadata mitigates the unexpected coding errors, design inconsistencies, data quality and code that is not well documented, and may be complex to read, understand and support.
• To establish a robust data acquisition environment, best practice design patterns are developed within the architecture of the metadata driven automation system.  These systems are architected by experts to leverage efficiencies in code, be flexible to different operational systems, optimally configured for disparate hardware, ensures maximum performance in run-times and quality is achieved.    

Movement to a metadata automation system delivers value to the customer in FOUR ways:

1. Replacing mundane human tasks of writing programs to load data with system generated code.  Manual coding tends to be repetitive and requires design governance and additional quality assurance.
2. The metadata driven logic is always consistent, of quality and optimized since the human error is minimized. Provides for more consistency, quality and streamlining of code as it is system generated.
3. Automatic creation of code reduces costs as the code is managed in bulk and not one object at a time.  This allows for maximum scalability, timely delivery, mitigates project risks and streamlines resource allocation.
4. Allows expert resources to focus on complex data manipulation and transformation to deliver optimum value to the customers.

WynTec has established the services of A2B Data™ and is offering cohesive partnership with end-customers and active consulting vendors to marry the science of data automation with expert resource management.  A2B Data™ specifically manages the design and processes to perform the data extraction, load and customized management of target databases.  A2B Data™ was built by industry experts to ensure that best-practice disciplines, flexible design patterns, performance and quality is managed in all aspects of the service.  This product and services was developed specifically to automate the mundane and repetitive tasks found in extraction and load processes.  Automating the data acquisition components frees the expert resources to focus on more complex matters of data management and data transformations.   

As opposed to days and weeks to code data movement routines, A2B Data™ performs these tasks in minutes as it is codeless and generates dynamic logic to perform the tasks.  No longer is it necessary to create an ETL map for every source to target migration.  No longer is it necessary to manually develop the architecture, Change Data Capture (CDC), data extraction logic, data type translation, optimized loads and persists history of all changed data. 

These design and disciplines are automated with best-practice models built in A2B Data™ and the end-user navigates via point and click management of the meta-model.

WynTec has brought insight to customer data assets for over two decades, managing in excess of half a billion dollars of capital budgets in building solid data management frameworks both nationally and internationally.  By separating the art of modeling the architecture from the science of design and deployment, we have successfully dissected the components that can and should be automated.

WynTec’s partnership program is offering the metadata driven automation services to the progressive consulting firms or freelancer to bring value to their customers by arming their expert resources with A2B Data™.   The consultants can now offer outcomes measured and delivery based pricing to their customers to develop solid data management practices.   The marriage of consulting expert resources coupled with the metadata driven automation services of A2B Data™ creates the most rewarding business offering in managing customer’s data asset. 

The following statistics were measures captured for a customer transitioning from traditional methods of managing their data acquisition (using commercial ETL software) to leveraging the A2B Data™ services.

GRAPH 1: Illustrates the resource cost by object count:

GRAPH 2: Highlights the time to deliver the data to production by object count:

 

Whitepaper: “Why Automation is Not a Bad Word” Download