Network & Security

Emphasis on digital technology with Internet of Things (IoT), access to real-time data & adapting Artificial Intelligence through Machine Learning.

BUSINESS ACTIVITIES

IT INFRASTRUCTURE AND NETWORK SECURITY CONSULTING
SMARTCARD, CCTV AND SECURITY ACCESS SYSTEM
DATA & VOICE CABLE DISTRIBUTION – INFRASTRUCTURE DESIGN
IT TRAINING AND MANAGEMENT SERVICES
DATA CENTER DEPLOYMENT
ENGINEERING SERVICES
OUT-SOURCING SERVICES

INTERNET OF THINGS

OPERATIONALIZE YOUR DATA
DATA TRANSFORMATION
PREDICTIVE ANALYTICS & MACHINE LEARNING
OPERATIONALIZE PERFORMANCE IN REAL TIME

OPERATIONALIZED YOUR DATA

GET THE RIGHT DATA

Find and access all the data sources you need and ingest the necessary data into your cloud data lakes

ACCELERATE DEVELOPMENT

Speed up the development of your analytics data pipeline

COLLABORATION & AUTOMATION

Enchance your data user's productivity with analytics data pipeline recommendations.

PROMETE DATA GOVERNANCE

Deploy prebuilt data quality rules so you can easily handle the scale of big data to improve quality

DEPLOYMENT BEST PRACTISES

Follow the CI/CD process to deploy big data analytics pipelines and futher it with scaled production

DATA TRANSFORMATION

Data transformation is the process of converting data from one format to another, typically from the format of a source system into the required format of a destination system. Data transformation is a component of most data integration and data management tasks, such as data wrangling and data warehousing.

PREDICTIVE ANALYTICS

At its core, predictive analytics encompasses a variety of statistical techniques (including machine learning, predictive modelling and data mining) and uses statistics (both historical and current) to estimate, or ‘predict’, future outcomes. These outcomes might be behaviours a customer is likely to exhibit or possible changes in the market, for example. Predictive analytics help us to understand possible future occurrences by analysing the past.

MACHINE LEARNING

While machine learning and predictive analytics can be a boon for any organisation, implementing these solutions haphazardly, without considering how they will fit into everyday operations, will drastically hinder their ability to deliver the insights the organisation needs. To get the most out of predictive analytics and machine learning, organisations need to ensure they have the architecture in place to support these solutions, as well as high-quality data to feed them and help them to learn. Data preparation and quality are key enablers of predictive analytics.