Data Management & Insights

We help organizations realise their vision of data-enabled transformation into reality. We offer consulting & implementation services for the following data-centric initiatives:

  • Data Architecture
  • Data Governance
  • Data Catalog
  • Data Integration & Data Quality
  • Streaming Data Processing
  • Data Visualization & Insights

Our Capabilities

We offer implementation services in a wide-range of  platforms including out-of-the-box OEM platforms and open-source technologies.
  • Strategy & Design: We help formulating design strategies & models for Systems of Intelligence namely; data lakes, modern data warehouses, lakehouses etc. and Systems of Engagement i.e. modern visualization platforms
  • Core Implementation: We provide implementation services leveraging latest project development methodologies (AGILE, DevOps) with focus on automation.
  • Support: We provide maintenance and support services for existing data systems and systems implemented by us.

Why Datalogy?

Digital Transformation

Expert Skillsets

Industry Domain Expertise

Timely & Quality Delivery

Solution Accelerators

Blogs

Data-Driven Superlative Customer Experience

Consumers are increasingly seeking seamless digital experiences, particularly given that many of our daily needs can be addressed with a single click. As a result, many individuals have become accustomed to using digital, from purchasing goods online to making payments using banking apps. However, when it comes to buying insurance,

Read More »

Top 9 Ways AI Is Transforming the Retail Industry

With large-scale digitalisation, it’s safe to say that AI is becoming an indispensable part of our everyday life. A prominent example of the same could be, recommendations. If you are into buying e-books on Amazon, you’ll notice you get suggestions based on your recent purchases or you might’ve noticed how

Read More »

6 Steps that are Key to Data Preparation in Machine Learning

Typically, raw data cannot be used directly in predictive modelling projects like classification or regression. For algorithms to function, data must be in numbers, and statistical noise and errors must be corrected, while some algorithms impose requirements on data. Raw data, clearly, is prohibited by all means. As a result,

Read More »