Data engineering and business intelligence


Is your data ready to be used for better business processes?

Data transformation through assimilation, extraction, and governance

Companies spend considerable time and effort to make data ready for analysis. According to Gartner, more than 50% of the effort in any data science or reporting project is consumed by data engineering. This is because data is stored in siloed legacy systems, on local machines, or on social media support platforms.

Data engineering initiatives focus on data extraction, cleansing, integration, quality, and governance. Careful choice of technologies, as well as the right human skills, are needed to perform data engineering tasks.

At HGS Digital, we have a dedicated global data science and analytics practice with the right people, processes, prebuilt assets, and technology know-how to manage data and build meaningful reports.

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Data challenges everywhere

CDOs are tasked with managing data assets throughout the enterprise so that data is readily available for downstream reporting and analysis. They face several challenges in their efforts to be the data supplier for the organization. While some of the challenges can be solved with adequate staffing, others are difficult to surmount as their solution lies in the prevailing data culture in the organization. Following are a few of their challenges.

Data quality

About 88% of companies see a direct effect of inaccurate data on their bottom line, losing an average of 12% of their revenue (Experian). A good part of data engineering focuses on quality. Data quality suffers for many reasons:

  • Obsolete and duplicate data
  • Compliance and security issues
  • Merger and acquisition activities

Data architecture

The success of data engineering efforts depends on the right data architecture. Factors to consider when designing a data architecture include:

  • Choice of technology solutions
  • Scalability and future-proofing
  • Current data structure and processing capabilities
  • Advanced analytics capabilities

Business intelligence

Many organizations lack a holistic, enterprise-wide approach to managing their investments in business intelligence (BI). Several challenges need to be addressed:

  • Multiple BI tools used
  • Need for a self-service model
  • Data governance for trust in data
  • Real-time reporting capabilities

Here’s how we can help

Data engineering

We design a future-proof, scalable, cloud-based data architecture and developing data hygiene protocols to ensure high quality of data

Business intelligence dashboarding

We create data environments for self-service reporting and executive, department, cross-department, and mission-specific dashboards

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Want to kickstart your data transformation?

In our data science center of excellence (CoE) workshop, you can learn how to:

  • Identify business cases for setting up a CoE
  • Create a strategy and roadmap
  • Define timelines and arrive at an execution plan

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Launching a data-led transformation initiative?

Our workshops can jumpstart your transformation initiatives. We offer a Data Engineering & Cloud Data Strategy workshop.
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Need better data quality for your business?

Improve your data hygiene strategy and make better data-backed decisions. Learn from our experts at one of our workshops.
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Data and analytics services

HGS Digital provides end-to-end data and analytics services.

HGS brings extensive data and analytics expertise, along with in-depth domain proficiency, to help clients transform their businesses. We provide strategic CX and technology consulting, along with resources to implement end-to-end data and analytics solutions.

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