Data Engineering

Data is the new Oil

“Data management consumes 80% of the effort spent in analytics“

Businesses often fail to harness the power of data because it is collected and stored in various sources. Further, lack of standardization in data makes analysis a more challenging task.

Are you facing this problem?

Our team specializes in data integration and ETL (Extract, transform and load) and has successfully solved this problem across industries like Life Sciences, Healthcare, Manufacturing, Insurance, Banking. Our services include:

  • Database & Data warehouse
  • ETL / ELT
  • Cloud

Data warehouses

Data warehouses are used to store large quantities of historical data and enable fast, complex queries across all the data, typically using Online Analytical Processing (OLAP).

We have experience across a broad range of technologies/products including Snowflake, Databricks and others.

ETL

In Extract Transform and Load (ETL), extraction is performed to get data from heterogeneous source systems to the target system, which is typically a cloud-based data warehouse, for BI purposes.

Some of the trends we achieve using ETL are

  • Data Quality
  • Data Harmonization
  • Data Infrastructure Setup
  • Data Lake (On-Prem, Cloud, Hybrid) and more

Cloud

Cloud-based data warehouse providers such as AWS and Microsoft Azure enable us to orchestrate a network of remote servers and computing resources in the cloud to provide data warehousing functionality.

Visualization

Good visualizations make the client think and ask more questions

Data Visualization is the essential last step of any successful data driven decision-making process. Our solutions go beyond better representation of data and provide insights that trigger deeper analysis

Our Approach

We adopt the following approach to deliver our solutions to business requirements. We have delivered solutions to clients in Media & Communication, E-Commerce, Insurance, Education and Construction.

Data Visualization is the essential last step of any successful data driven decision-making process. Our solutions go beyond better representation of data and provide insights that trigger deeper analysis

Our Expertise

We specialize both in open source and enterprise tools. This breadth of knowledge allows us to choose the most cost- effective tool to deliver our solutions to client requirements.

Data Science

Our team of data scientists and data engineers have provided solutions in descriptive, predictive and prescriptive analytics using various machine learning techniques such as clustering, segmentation, modelling, etc.

Our Approach

Data is collected from different sources and stored in a repository. The collected data is cleaned and preprocessed before passing it to any machine learning model. Exploratory Data Analysis plays a vital role in the whole process. This will help us understand the data better.

Data is not just about:

  • Statistics
  • Machine Learning
  • Visualization
  • Wrangling

Data is about understanding. Understanding the problem and how we can solve it using data with whatever tools or techniques we choose.

Once the data is cleaned and explored, we must create new features (Feature Engineering). This requires domain knowledge to come out with relevant features. Based on the problem statement, appropriate machine learning techniques can used like classification/regression/clustering. Once the model is built, this must be tested and validated in a different dataset and then it can be deployed in production.