Digital Transformation & Software Engineering Services
Artificial Intelligence Culture

Building a Data-driven and Artificial Intelligence Culture in the Enterprise: A Winning Formula

At Ness, our enterprise customers are eager to explore their hidden treasure in the data that they have generated over the years. Market research shows a growing demand for data monetization, and estimates that the Big Data market will be $125B (USA, including hardware, software and services) by 2025 [Source: Million Insights]. In 2014, Big Data […]read more »
Data Vault

Is Data Vault Modeling a Good Choice for Your Organization?

As business environments get increasingly volatile, enterprise data architectures must be flexible and adaptable to fast changing market conditions. The common challenge with dimensional and normalized data modeling techniques is that they aren’t designed to respond to fast changes. Data Vault modeling helps address this challenge. Data Vault architecture is an innovative, hybrid approach that […]read more »
Autonomous driving

Sensor Fusion Algorithms For Autonomous Driving: Part 1 — The Kalman Filter and Extended Kalman Filter

Introduction Tracking of stationary and moving objects is a critical function of Autonomous driving technologies. Signals from several sensors, including camera, radar and lidar (Light Detection and Ranging device based on pulsed laser) sensors are combined to estimate the position, velocity, trajectory and class of objects i.e. other vehicles and pedestrians. A good introduction to […]read more »
JavaScript AngularJS framework

Representation of large corporate data in HTML tables under JavaScript AngularJS framework

In corporate or enterprise platforms, the representation of tabular data in single-page web apps is a common occurrence. There are challenges with the amount of data rows, the variety of data types, and number of simultaneous columns enterprise users wish to see. In addition, the perceived performance of tabular data in a client-side web application […]read more »

Cascading Lingual Makes it Easy to Migrate Enterprise Data Warehouse (EDW) to a Hadoop Data Lake

In the world of Big Data, companies are increasingly leveraging Cascading Lingual to facilitate the adoption of enterprise Hadoop because it makes it easy for SQL users to utilize their existing skills to quickly create and run applications on Hadoop. Bhushan Pargaonkar, Lead – Technical, explores Lingual’s heritage and the reasons that make it the […]read more »
Big Data Initiative

Don’t Be Fooled By Facades

When NoSQL databases first appeared, in response to the need to process high volumes of unstructured data, the “o” in NoSQL was small, and it meant that these systems had “No” SQL support – SQL was meant for traditional structured relational databases, not these new schema-less contraptions. But, developers know and love SQL, so these […]read more »

The Nomadic Nature of Data

Unfortunately for most businesses, there is no promised land for Data: no single end location that provides everything your organization needs to unleash the potential of its data assets. Data is inherently nomadic, and the notion of storing data, either in a centralized store or decentralized stores, is constantly evolving to support business and technology […]read more »