search icon
Data Analytics Services

Actionable Data Insights

Overview

In the world of artificial intelligence, everyone knows the importance of data. However, not all data is created equal. Actionable data is a crucial asset for decision-making in addition to domain knowledge. It consists of data that is not raw but relevant and meaningful and can empower organizations to make well-informed decisions to achieve business success.

The data-driven AI-based solutions can be primarily grouped into 2 categories. They are as follows:

Decision support systems: The human agent uses the insights provided by the algorithms in the decision-making process

Decision-making systems: A virtual agent makes autonomous decisions

With technological advancements and multiple data sources, data analytics services that furnish actionable data will rise and evolve. Data-driven enterprises will have a competitive edge over others for continued success. Let us see how Hughes Systique can help.

Expertise

Over the years Hughes Systique has built a strong portfolio of AI/ML-powered offerings and helped its customers streamline their business processes, empower decision-making, and enable business growth.

AI-Driven Data Analytics Services:

HSC offers Data analytics services that convert raw data into actionable insights. Take a look at what we offer to our multitude of enterprise customers:

Data Visualization:

Develop dashboards for operations with easy-to-understand visualizations. These will help the operations team understand what is happening and take action if necessary.

Business insights:

Slide and dice the data for different parameters, try to establish dependency between outcomes & observed parameters and help the business teams make crucial decisions

Forecasting:

Analyse time series data, and develop models/applications to forecast outcomes of interest.

Technical Expertise:

Our data analytics services offerings are backed by the triad of tools, technology, and techniques.

Tools:

Python/Pandas/Numpy, R, PowerBI, Tableau, Statsmodels, Matplotlib, FBprophet etc.

Technology:

Big data (Batch & Stream Processing), Data lake & warehouse, Databases (SQL & NoSQL), Data-mining to name a few

Techniques:

Regression, classification, Prediction, Recommendation, clustering, TOP (Trend, Outlier, Pattern) Analysis, statistical analysis, and time-series forecasting are some of the popular techniques

Use Cases:

Here are a couple of projects where HSC showed exceptional depth of knowledge in gleaning insights from data and completed the assignment for favorable business outcomes:

Battery health analysis:

This involves analyzing the KPIs reported by sensors on the solid-state battery, forecasting the battery’s service life, and suggesting proactive maintenance and replacement.

Network KPI analysis:

Trend, outlier & pattern analysis of the statistics reported by the network, flag anomalies in the performance of HW modules & help in fault isolation

FAQs

Resources

×

Enquire Now


We will treat any information you submit with us as confidential

arrow back top