Data Analytics and Artificial Intelligence Consultancy

Data Analytics and Artificial Intelligence Consultancy is a service that helps businesses analyze large amounts of data to gain meaningful insights and improve business processes using artificial intelligence (AI) technologies.

This service is used to improve data-driven decision-making processes, optimize business operations and provide competitive advantage.

Data Analytics Services

Data analytics is a process that aims to gain insights by analyzing large data sets. The main areas are:

✅ Descriptive Analytics – Understanding what happened based on past data.

✅ Predictive Analytics – Using past data to predict future events.

✅ Prescriptive Analytics – Performing analysis to determine what actions should be taken.

✅ Real-Time Analytics – Providing instant insight by processing instant data.

✅ Customer Analytics – Providing better service by analyzing customer behavior.

✅ Financial Analytics – Monitoring the financial health of the company and managing risks.

Technologies Used: Python (Pandas, NumPy, Scikit-learn), R, SQL, Apache Spark, Power BI, Tableau

Artificial Intelligence and Machine Learning Services

Artificial intelligence takes data analytics a step further, enabling machines to learn, predict, and automate.

✅ Machine Learning (ML) – Making predictions by learning from data with algorithms.

✅ Deep Learning – Analyzing complex data sets using neural networks.

✅ Natural Language Processing (NLP) – Obtaining automatic insights by analyzing text and speech data (e.g. chatbots, sentiment analysis).

✅ Computer Vision – Performing analysis on images and videos (e.g. facial recognition, object detection).

✅ Recommendation Systems – Providing user-specific recommendations (e.g. Netflix, Amazon recommendation engines).

✅ Anomaly Detection – Fraud detection, quality control, network security, etc. areas.

Technologies Used: TensorFlow, PyTorch, OpenAI GPT, Scikit-learn, Keras, OpenCV, NLTK, Spacy

• 📊 Data-Based Decision Making: Correctly analyzed data enables more accurate business strategies to be created.
• ⚡ Operational Efficiency: Saves time and costs by automating business processes.
• 🎯 Personalized Experiences: Provides the opportunity to provide more personalized services by better understanding customer needs.
• 🔍 Risk and Fraud Detection: Used to detect fraud in sectors such as finance, insurance, and banking.
• 📈 Sales and Marketing Optimization: Increases sales with target audience analysis and customer behavior predictions.

Stage 1: Needs Analysis

• The business's data management processes and existing technologies are analyzed.

• Goals are determined (e.g. reducing customer churn, detecting fraud, optimizing marketing campaigns).

Stage 2: Data Collection and Cleaning

• Data is collected from various sources (CRM, ERP, IoT devices, social media, sensors, etc.).

• Data cleaning and preprocessing processes are performed.

Stage 3: Analysis and Modeling

• Data analytics techniques are applied.

• Machine learning algorithms are trained and tested.

Stage 4: Reporting and Providing Insight

• The findings are presented to the business units.

• Visualizations are made with tools such as Power BI, Tableau.

Stage 5: Implementation and Integration

• Artificial intelligence models are integrated into the business's systems.

• Continuous monitoring and optimization are performed.

✅ Finance and Banking: Fraud detection, credit scoring, customer segmentation

✅ E-Commerce: Recommendation systems, price optimization, customer behavior analysis

✅ Healthcare: Disease prediction, patient data analysis, drug development

✅ Manufacturing: Production line optimization, quality control, maintenance prediction

✅ Logistics: Supply chain optimization, route planning

✅ Retail: Customer analysis, sales prediction, inventory management

✅ Energy: Smart grid management, energy consumption prediction

👨‍💻 Technical Competencies

• Python, R, SQL, Hadoop, Spark
• Machine learning and deep learning algorithms
• Data cleaning and big data management
• Advanced statistics and mathematics

📊 Business and Consulting Competencies

• Business intelligence tools (Power BI, Tableau)
• Industry knowledge and business analytics
• Creating a data strategy
• Communication and reporting skills