What is Advanced Analytics?
Advanced Analytics is the evolution of data analysis, combining sophisticated techniques such as Artificial Intelligence (AI), Machine Learning (ML), and statistical modeling to uncover deeper insights, predict future trends, and optimize decision-making.
Our team transforms your data into a powerful strategic asset, helping your organization react to changes in real time, shape strategies for the future, and innovate.
How Advanced Analytics Drives ROI
Advanced Analytics empowers businesses to act rather than react, unlocking new growth and long-term impact.
By simulating “what-if” scenarios, Advanced Analytics proactively manages risk and minimizes disruptions, helping organizations stay ahead of change.
Trust us to help you uncover new revenue opportunities and deliver personalized experiences at scale.
Our Solutions
Forecasting
Measure Tomorrow with Precision.
Forecast future trends in sales, operations, and finance with precision and confidence, minimizing risk and enabling informed strategic planning.
Our AI-driven software adapts to your unique needs, ensuring that your forecasts are accurate, actionable, and easy to implement across your organization.
AI-Driven Decision-Making
Go beyond prediction with AI-powered recommendations that suggest the best course of action for optimal results.
AI-driven decision-making doesn’t just tell what might happen; it provides data-driven insights on what to do next, ensuring that our decisions are optimized for maximum efficiency and impact.
Optimization Solutions
Enhance your supply chain (SC) and operations by leveraging advanced algorithms to minimize costs, improve services, and boost speed.
Our optimization solutions empower your organization and enhance business value by using highly sophisticated AI-driven methodologies.
Agent-AI & Auto-ML
Automate complex processes and uncover deeper insights with cutting-edge AI and machine learning models tailored to your industry needs.
No matter where you are in your analytics journey, WITSIDE’s services are designed to drive impactful results across your organization by using the latest methodologies and infrastructure.
Case Studies
See how we’ve helped companies in Greece and abroad achieve digital transformation across leading industries, including energy, oil & gas, retail, and tourism.
- BI, Data Management
- Advanced Analytics
- BI, Data Management
Transform Your Data with WITSIDE’s AI and ML Solutions
Unlock the next level of data-driven innovation by integrating AI capabilities into your analytics strategy.
Our expert team harnesses advanced ML algorithms to deliver automated, data-driven insights that continually adapt and evolve with your business.
From automating complex forecasting processes to uncovering hidden patterns in vast datasets, our solutions empower you to stay ahead of market changes, enhance the customer experience, and drive sustainable growth. We help you achieve:
- Greater accuracy and predictive power
- Reduced manual effort and faster decisions
- A competitive edge by transforming data into actionable insights
Tools & Technologies We Use
We leverage the best data analytics tools to predict the future and drive business success.
Qlik Predict™ helps analysts predict trends, understand causes, make proactive decisions and drive results – no coding needed.
Microsoft Azure provides storage, analytics, AI and more, enabling businesses to build, deploy and manage applications securely.
Forecast pro is an off-the-shelf forecasting package used across virtually all industries, enabling everyone to leverage sophisticated forecasting techniques.
Alteryx offers a leading AI Platform for Enterprise Analytics that delivers actionable insights by automating analytics.
Want to learn more?
What Our Clients Say
FAQs
What are the common challenges companies face with forecasting?
Companies often struggle with key questions such as:
🚀 How accurate is our forecasting? Can we improve it?
🚀 Are we using the most effective algorithms?
🚀 How can we reduce the time and effort required to generate forecasts?
🚀 How predictable is our product portfolio, and at which level?
🚀 Can additional external data enhance our forecast accuracy?
🚀 Is there a platform that integrates our forecasting process across teams while remaining cost-effective?
At WITSIDE, we address these challenges by offering end-to-end forecasting solutions that combine internal historical data with external (exogenous) data.
This approach significantly enhances the accuracy of forecasting models, providing businesses with actionable insights and measurable improvements.
What tools do you use for advanced analytics?
At WITSIDE, we leverage various advanced tools depending on the project requirements. These include:
🚀 AI and Machine Learning Platforms: Such as Microsoft Azure for predictive modeling and automation.
🚀 Data Integration & ETL Tools: Such as Alteryx for data preparation and integration.
🚀 Statistical Analysis Software: Including R and Python for data analysis, predictive modeling, and statistical algorithms.
🚀 Visualization Tools: Such as Qlik, Power BI, and Tableau to help stakeholders visualize insights and outcomes.
Which industries can benefit from advanced analytics?
Retail: For demand forecasting, customer segmentation, and personalized marketing.
Finance: For fraud detection, risk management, and customer retention.
Healthcare: For predictive diagnostics, patient care optimization, and operational efficiency.
Manufacturing: For predictive maintenance, supply chain optimization, and quality control.
Logistics: For routing optimization, demand planning, and efficiency improvements.
Telecommunications: For network optimization, customer churn prediction, and targeted marketing.
Do I need a data science team to implement advanced analytics in my organization?
Not necessarily. While having a dedicated data science team can accelerate adoption, it’s not a requirement. Many organizations can collaborate with a reliable advanced analytics company like WITSIDE to deploy Advanced Analytics solutions. This option reduces the need for deep in-house expertise, enabling business users to access advanced insights with the help of intuitive software and expert external support.
What is the difference between analytics and advanced analytics?
Analytics focuses on analyzing historical data to understand what happened and why. It typically includes descriptive and diagnostic methods, like basic reporting and data visualization.
Advanced Analytics goes beyond this, using predictive modeling, machine learning, and AI to forecast future trends, optimize operations, and recommend actions. It’s proactive, helping businesses not only understand past performance but also shape future outcomes.
What’s the difference between business intelligence and advanced analytics?
Business Intelligence (BI) primarily focuses on descriptive analytics, which looks at past and present data to understand what happened and present those insights via dashboards and reports.
Advanced Analytics, on the other hand, focuses on predictive and prescriptive analytics, using data to forecast future outcomes and recommend specific actions to optimize business processes. Advanced Analytics delves deeper than BI by uncovering patterns and making data-driven recommendations for future decisions.
What’s the difference between advanced analytics and artificial intelligence?
Advanced Analytics uses data analysis techniques like predictive modeling, machine learning, and statistics to forecast future trends and optimize decision-making.
Artificial Intelligence (AI) is a broader concept that refers to machines simulating human intelligence. AI can include machine learning, natural language processing, and automation, and Advanced Analytics often uses AI techniques to generate predictions and recommendations. Essentially, Advanced Analytics can be considered a specific application of AI to analyze data and drive business insights.
What's the difference between data science and advanced analytics?
Data Science is a broader field that encompasses the entire process of extracting insights from data, including data collection, cleaning, analysis, and interpretation. It involves a wide array of methods, including machine learning, artificial intelligence, and statistical modeling.
Advanced Analytics is a subset of Data Science focused specifically on sophisticated techniques like predictive modeling, optimization, and AI-driven decision-making analytics to drive business decisions and forecast future trends.
Business Intelligence
Transform complex data into intuitive, interactive dashboards that empower decision-makers to uncover actionable insights and drive business success with clarity and precision.
Data Management
Ensure data integrity, accessibility, and compliance with robust management strategies, unlocking the full potential of your data for smarter, more informed decisions.
