3 Key Topics: Digital Business, Enterprise Modernization, & EQengineered

Fireside Chat with EQengineered’s Chief Data Officer, Ranjan Bhattacharya.

1.    As enterprise organizations continue their data journeys and become digital businesses, what are the key data engineering areas on which they should focus to enable growth and the ability of the enterprise to compete and thrive?

Building an enterprise-wide data architecture requires multi-year investments, and a sizable team comprising skilled but hard-to-find experts. Traditional data warehouse, ETL, and reporting tools are expensive and often hard to adapt to the challenges of a modern enterprise data needs, related to volume, and variety of formats.

Our recommendation would be to build such data pipelines using cloud-based data platforms. That way it is possible to start small, and inexpensively, focusing on a small slice of the business. Cloud-based tools are easier to set up and can handle a broader variety of data and integration formats. As people get more expertise on cloud platforms, it becomes more and more of the organization can be migrated with relatively minimal efforts.

In addition, it is critical to build the necessary skills not only for data science and engineering, but also have people trained on cloud offerings that are directly related to data processing.

2.    There is a lot of enterprise discussion about modernization. What are the key data engineering challenges being faced in today's environment and how can organizations overcome these obstacles?

Turning data into actionable intelligence is not an easy task; it is a journey with many challenges along the way. Here are some questions that may help identify some of these challenges:  

·      Data availability: is the right data available? Will it drive the right insights and outcomes?

·      Data hygiene: how clean and up to date is the data which is driving business intelligence?

·      Data consistency: do different departments, operate in silos, having different representations and interpretations for the identically named entities, like a customer?

·      Data security, privacy, and compliance: with increasing regulatory scrutiny, and reputational risks, how secure is the data, particularly with regards to privacy and compliance.

·      Data governance, and ownership: is there clear definition of data ownership across the enterprise? Is data governance helping or hindering innovation?

·      Technical and business skills: do you have people or are you planning to hire people who have the necessary skills for cloud-based data engineering?

It is also important to realize that even if the best data and processes are available, analytics is fundamentally subjective and requires an iterative and agile approach.

3.    Who is EQengineered, what are EQengineered's core competencies, and what makes EQengineered unique in the marketplace?

The EQengineered team strives to connect with our clients' goals, priorities, and milestones so we can deliver outcomes that solve real world problems. We structure our engagement with the big picture in mind, with short, medium and long term goals.

Our core competencies are in data architecture, data analytics and management, and cloud migrations, in addition to building customer and user experience flows, and application architecture and implementations.

We employ agile development processes throughout the engagement, showing concrete progress along the way.

What makes us unique is our ability to offer practical solutions to organization-wide problems through short, focused engagements which can deliver outcomes within a broader long-term roadmap.