Rethinking data platforms to enable digital transformation.

Rethinking data platforms to enable digital transformation

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Data Engineering

Why Data Engineering ?

Did you know that 80% of the time taken across all AI projects consist of data engineering and preparation tasks? That's right. With the deluge of data, data engineering services are in higher demand in 2020. The volume of data has grown dramatically, while the cost of compute and storage have dropped, and algorithms have become freely available. With the right approach to Data Engineering, organizations can monetize and maximize the value of their data assets by creating a strong foundation of data and incorporate insights from data science into their daily business processes. However, organizations must confront some key issues if they want to truly exploit these opportunities and transform themselves into analytically savvy competitors.

Data Engineering Services

Why LatentView for Data Engineering?

Business-focused analytics


Business-focused approach to data engineering to align analytics and technology.

Scalable modern architectures


Workload-centric architectures to meet different needs of business stakeholders.

Global talent


Proven experience in delivering analytics solutions to internet-scale companies using Hadoop and open source technologies, on-premise and on-cloud.

Peer Learning

Deliver scalable real-time analytics with Apache Pinot

deliver scalable real time analytics 1

Ever wondered how to achieve ultra-low latency on a realtime distributed OLAP datastore? The wait is over!...

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Data visualization and exploration with Apache Superset

Apache Superset Final presentation 1

Apache superset is a modern data exploration and visualization platform. It is an open-source alternative to...

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Feast: The future of feature engineering

feast peer learning deck 1

Feast (Feature Store) being an operational data system is used for managing and serving machine learning...

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Analytics Zoo – End to End Analytics and AI Platform for Apache Spark

Analytics Zoo End to End Analytics and AI Platform 1

Analytics Zoo makes it easy to build machine learning/deep learning applications on Apache Spark and BigDL,...

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The Neo4j Series: Playing with Graphs

The Neo4j Series Playing with Graphs 1

Neo4j is a native graph database that is highly efficient and responsive due to the perpetual storage...

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Deploy Spark/ML Jobs on Kubernetes using Dockers

Spark on Kubernetes using Dockers 1

Apache Spark is a data processing framework that can quickly perform complex processing tasks on very...

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Data Workloads with Snowflake and DBT

Dataworkloads with Snowflake and DBT 1

Snowflake is a data warehouse provided as a Software-as-a-Service (SaaS) that is faster, easier to use,...

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Redshift Optimization

Redshift Optimization 1

Amazon Redshift is a cloud-based data warehouse that makes it fast, simple, and cost-effective to analyze...

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Drift Detection on Cloud Formation

Drift Detection on Cloud Formation 1

AWS CloudFormation gives you an easy way to model a collection of related AWS and third-party...

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Dr. Elephant for Spark Optimization

spark optimization dr elephant 1

Dr. Elephant is a performance monitoring and tuning tool for Hadoop and Spark. It automatically gathers...

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ACID Compliance on Data Lake using Apache Hudi

acid compliance apache hudi 1

Apache Hudi is an open-source data management framework used to simplify incremental data processing and data...

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CI/CD Implementation using Azure DevOps

azure devops 1

Azure provides rich DevOps services to automate the deployment of code & infrastructure into production. In...

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Capturing Social Media Data using API

capturing social data using api 1

APIs (Application Programming Interfaces) allow us to ingest data from external unstructured data and integrate data...

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An asynchronous programming library in Python

asyncio python 1

In this session, we will explore how we can call functions now and then receive results...

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Azure Function – Technical Overview

azure functions 1

Azure Functions is a serverless compute setup available in the Microsoft Azure ecosystem. It is the...

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AWS – Practical DevOps

practical devops aws 1

AWS’s rich solution components allow engineers to automate processes end to end. Automation allows us to...

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Talend – Data Integration in the New Age

data integration in the new age talend 1

Talend enables us to extract diverse data assets flowing at different velocities (batch & stream), transform,...

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Kafka – Does it really follow the order?

apache kafka does it follow order 1

Apache Kafka is the goto distributed event streaming platform of choice for handling high throughput &...

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Essentials of Apache Hive

apache hive essentials 1

Apache Hive is an open-source data warehouse built on top of Hadoop for analyzing data at...

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Architect modern analytics architectures for the age of big data, cloud and IoT. To know more about Data Engineering, write to us at

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