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services – Data Engineering

building data solutions for a
smarter tomorrow

a quick overview

Modern organizations grapple with vast, often fragmented datasets hindering valuable business knowledge extraction. Our team of skilled data engineers and consultants specializes in architecting high-performance data infrastructure, implementing advanced optimization techniques to transform raw data into a cohesive, readily analyzable format. Our data engineering practice accelerates the data to decisions continuum, bringing competitive advantage to businesses.

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services

data architecture

Our team of certified data architects crafts high-performance DE cloud solutions. We specialize in automating ETL processes, optimizing database & data warehouse platforms, and developing software for seamless integration.

data processing

Our expertise spans in real-time & batch data pipelines. We ensure data quality through data standardization services. From Data lakes to warehouses, we configure storage for both structured & unstructured data.

data analytics

We offer consultancy to develop analytical methods, build recommendation systems, & extract patterns from sequential data. Additionally, we provide quality evaluation services to optimize organizations’ analytical products.

steps to data engineering

1

data acquistion

Data is extracted from various sources such as databases, APIs, & files. Data is cleansed & preprocessed
to ensure accuracy, with data governance practices implemented to manage access and security.
2

data transformation

Raw data undergoes ETL processes to transform it into usable formats. Data from multiple sources is integrated
to create cohesive datasets, incorporating enrichment techniques like feature engineering.
3

data processing & analytics

Batch and real-time data processing pipelines are developed using tools. These pipelines perform aggregation, summarization, & statistical analysis, with ML applied for deeper insights.
4

data quality assurance

Rigorous data validation & quality checks are applied to ensure data accuracy & reliability. Monitoring of data pipelines & performance metrics is conducted to address issues.
5

deployment & monitoring

Data pipelines & systems are deployed to production environments, with alerting mechanisms in place to detect anomalies. Regular maintenance to ensure system reliability.

see the proof of our data engineering work

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Optimizing beverage SKU pricing with data analytics

Problem statement: Our beverage company offers a variety of SKUs,…

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Transformative data engineering for a major retail chain

Background: Client: A very large retail chain which is a…

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Accelerating monthly data analysis with generative AI

Problem statement: Top executives require timely insights from monthly data…

struggling with
data silos & complex
data workflows?

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