Black Basil Technologies



database administrator

Data Engineering

We have deep experience in Data Engineering in which we design, build and maintain the infrastructure required for the collection, storage, processing, and analysis of large amounts of data. Our engineers develop pipelines that move data from multiple sources, transforms and cleans the data, and loads it into databases or data warehouses.

Leveraging data engineering, we aim to create an infrastructure that may deal with large volumes of data. We setup and maintain this infrastructure required to support information driven decision making. In addition to that we develop and deploy machine learning models and other advanced analytic purposes.

We follow different paradigms, strategies, architectures, principles to achieve our goal of providing useful data in the hands of key decision makers which eventually helps businesses to grow faster.

We specialise in building ETL Pipelines which involves high volume of data.

We provide services to setup Data Warehouse, Data Lake, Data Lakehouse, Data Mesh architectures. We devise right strategies for Data Modelling, Data Management, Data Governance and Data Quality, ensuring business get the benefit from adopting data capabilities


We are the specialist in AI (Artificial Intelligence) and ML (Machine Learning) which involves the development of intelligent systems that can achieve the similar capabilities that typically require human cognitive skills, such as perception, reasoning, learning, and decision-making.

Leveraging AI, we use the range of techniques, including rule-based systems, expert systems, natural language processing, speech recognition and computer vision, among others. Leveraging ML, which is a subset of AI, we make use of statistical and computational techniques to enable machines to learn from data, without being explicitly programmed

We use ML algorithms to build models on available date to make predictions or classifications on new data. Some common types of ML algorithms include Linear Regression, Logistic Regression, Decision Tree, Random Forest, XGBoost, Artificial Neural Networks (CNN, RNN)

We solve the problems in a variety of industries, including healthcare, finance, retail, and manufacturing, harnessing the the power of AI to enable automation, improve decision-making, and enhance efficiency.

Data Analytics

We have extensive experience in Data Analytics. We help in making the discovery of useful information, informing conclusions, and supporting decision-making simpler following the process which involved inspecting, cleansing, transforming, and modelling data

Data analysis which has multiple facets and approaches, we use diverse techniques and leverage that in different business, science, and social science domains, 

Generally we follow these steps: BI Strategy and Roadmaps, Data exploration and Discovery, Data-Driven Innovation, Data Visualisation and Reports, Total cost ownership optimisation, Analytics Cloud.

Tech Stack


Amazon Web Service
Microsoft Azure
AWS google cloud
Amazon Redshift
Amazon Sagemaker


Python Icon
Scala Data

BI and Visualization Tools

tableau Logo
Power BI data analysis tool
Data Studio Tool for Analytics
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Azure Machine Learning
TensorFlow Logo
Bigml Data
Plotly Data
Seaborn Logo
Matplotlib Logo
PyTorch Logo
Keras Logo
Jupyter Logo
Scikit Learn