AI Consulting

DataX delivers end-to-end AI and big data analytics work for your organization. We will partner with you to start defining your organization’s AI strategy. And, together, we can work our way down the analytics funnel to incorporate data engineering, data analytics, reporting and visualization, and the deployment of your data-driven systems.

AI Strategy

Before developing an AI product or solution, it is important to understand why you are doing it. Is it to increase revenue, decrease cost, or drive efficiencies? AI and big data analytics is about strategy and not technology, as many are led to believe. Artificial intelligence begins with your organization’s goals, which would then cascade down to business cases that would exploit this disruptive technology.

For example, a manufacturer’s goal may be to improve their production operators’ productivity and safety by observing and correcting their posture and movements in the shopfloor. Once this goal has been established, only then would the manufacturer figure out how to exploit the data they currently have and use AI to analyze how their operators behaves and moves around. The insights generated by AI would then be used to improve the workers’ wellbeing and productivity.

We offer AI strategy formulation which include the following:

• Establishing your AI goals
• Determining your current AI maturity level
• Exposing high-value AI-driven business cases
• Developing an immediate and long-term AI blueprint

Data Engineering

Data engineering refers to the extraction and ingestion of raw data from various sources and transforming this data into formats that can be analyzed by AI algorithms.

It is very common for the source data to be dirty. You may run into missing data. You may encounter data that is not harmonized. For instance, there are over 50 ways to spell the city “Kuala Lumpur” (“KL”, “K/L”, “K. Lumpur”, etc.). So, all these variations of “Kuala Lumpur” entered by users must be standardized. You may also come across typos in the data you are trying to ingest. Or outliers (a user might have accidentally keyed in “250” as her age).

The purpose of data engineering is to ingest and clean up data from multiple sources so that your AI algorithms can work on them.

Our data engineering services include:

• Data extraction and ingestion from multiple internal and external data sources
• Data transformation and data cleansing
• Data warehouse design
• Loading clean, granular data into the data warehouse for AI and data analytics

Data Science & Analytics

Artificial intelligence is about making machines smart through algorithms. Older AI models were built using expert systems and statistical learning. As technology progressed, machine learning algorithms such as supervised learning, unsupervised learning, reinforcement learning, and deep learning were created.

Once you have clean data sitting in your data warehouse, you can then design your AI or analytics model. An example would be an e-commerce product recommendation AI algorithm that takes people with similar demographics and behavior and tries to predict products that will interest them.

We offer the following data science and analytics services to facilitate intelligence machines:

• Expert systems
• Statistical learning
• Machine learning
• Deep learning

Data Visualization

Reports and dashboards are output produced from your analytics. They must communicate critical insights and allow you to take action. Otherwise, these reports would have been generated for nothing.

For example, one of the many crucial reports generated by an e-commerce product recommendation AI model would be a matrix of product recommendations and the propensity of users to purchase them. This report tells the e-commerce platform owner the products that should be recommended whenever a specific users logs into the platform!

We offer the following dashboard and data visualization services:

• Report / Interactive dashboard design and implementation in Tableau and Power BI
• Report / Dashboard optimization
• Data storytelling consultation

DevOps Services

DevOps are your software development and IT operations people who will help you operationalize your AI models. Take, for example, e-commerce product recommendation. Data engineering would ingest and clean customer and transaction data. Data scientists would then provide the product recommendation model.

But we can’t just stop there. The AI model must be deployed and operationalized. The product and customer purchase propensity matrix generated by the model must be fed into your e-commerce platform as product recommendations. That’s where DevOps come into play. They will do the work of linking the output from your analytics model to the e-commerce platform so that users can see these product recommendations.

DevOps are the final link to operationalizing and driving ROI from your analytics. DevOps services offered by us:

• Product development (plan, develop, test, and deploy)
• Product update delivery
• Software performance monitoring and logging

Projects Done With Clients

DataX’s data professionals have cumulatively delivered many successful AI and advanced analytics initiatives for clients in a variety of industry sectors. Below is a list of projects completed for our customers: