The Power of Data: The New Digital Treasure
Every second, an incredible amount of information is generated from a variety of sources, including social media, the internet, call centers and sensors. This data, which comes in various forms, must be analyzed and processed in order to provide a global vision of business and optimize processes based on real and reliable information.
It’s estimated that in 2020, around 1.7 MB of information per person in the world will be created each second. The most common applications of Data Science focus on user segmentation and personalization, predictions, decision-making, recommendations, advanced analysis and visualization of data models. The value of the Big Data market will reach $118.52 billion by 2022, with an annual growth rate of 26% from 2015 to 2022.
Data Science
- The use of past patterns to predict the future.
- Data from various sources.
- Tied to machine learning to extract information.
- Aimed at improving production processes.
Data Analytics
- The extraction of information from past patterns.
- Data from a single source.
- Testing of raw data to draw conclusions.
- Uses different programming languages to extract information from the data: R, Python, etc.
- Verifies/refutes existing theories and models.
Data Science
The knowledge behind the data: looking at the future.
Data science involves methods, processes and systems to extract knowledge or improved understanding of information from multiple sources and in various forms, whether structured or unstructured. It includes the cleansing, preparation and analysis of data.
Having access to customers’ information (behavior, preferences, interests, etc.) allows companies to anticipate their needs and provide 360° support with a comprehensive UX that meets expectations.
- We include all kinds of data from any source in order to gain a global vision of the entire business.
- We use advanced machine learning algorithms to detect patterns in the data.
- We analyze the data and extract critical insights, then offer the best possible visualization of them to facilitate decision-making.
Customer segmentation and personalization.
Optimization of business processes.
Improved machine and device performance.
Improved security and fraud detection.
Financial trading and equity investments.
Creation of custom products and services.
Optimization of intelligent decision-making.
Creation of more efficient processes to reduce costs.
Our work process:
1. Inventory of business questions: the information collected must respond to the needs identified.
2. Data collection and extraction: search for data that will help to answer all of the questions posed. The data may come from different sources, and if there are several, we must unify the information in a reliable and structured way.
3. Data processing and organization: once the data has been collected, the processes of data cleansing, standardization, processing and organization are carried out in order to avoid inconsistencies.
4. Data Analysis: there are several types of analysis, including pre-processing, creation and optimization of models, predictive analytics, machine learning and statistics.
5. Development of models and algorithms: these are used to find standards and patterns beyond normal human perception. They analyze millions of scenarios in a matter of minutes, allowing for more assertive decisions to be made in a short period of time.
6. Data Visualization: visual analysis of the results guarantees that the conclusions of the analysis are fully aligned with the study’s objectives. This is achieved through graphics that make it easier to identify standards and make decisions.
7. Decision-making: the presentation of insights and recommendations for strategic decision-making based on the data analyzed.
Essential prerequisites for analysis:
- Centralized distribution of data.
- Reinforcement of its consistency.
- Elimination of redundancy.
- Privacy protection.
- Regulatory compliance.
- Secure access to data.
- Quality assurance.
Data Analytics
Revealing trends and metrics to increase & boost business systems efficiency and performance.
This discipline procures ideas from sources of unprocessed information through data analysis. It reveals trends and metrics, using the conclusions reached to increase the efficiency of a business system, improving strategic decision-making and enabling increased business volume.
- Improve operational efficiency.
- Improve and optimize the client’s user experience.
- Perfect the business model.
Enables real-time business analysis: it makes the most of information by using devices that allow you to analyze what’s happening with the business at any given moment.
Fosters greater business efficiency: uses data to increase return on investment. Allows companies to create new KPIs and analyze them more broadly and objectively, in order to improve profitability levels.
Business Experiments
Business experiments, experimental design and A/B testing. Techniques to test the validity of decision-making.
Visual Analytics
Images or graphics used to represent data and detect patterns. Data analysis + visualization + human interaction.
Correlation Analysis
Statistical technique to determine if there’s a relationship between two independent variables, and to quantify its strength.
Forecasting
Data collected at evenly spaced intervals. Time series analysis to predict future events based on what has happened in the past.
Scenario Analysis
Total return analysis allows us to analyze a variety of possible events and future scenarios, considering the potential alternative results.
Regression Analysis
A statistical tool used to study the relationship between variables, and to determine if one variable may be affecting another.
Data Mining
An analytical process that explores large data sets to find relevant ideas, patterns or relationships that can optimize efficiency and performance.
Text Analytics
Text Mining. The extraction of value from large volumes of unstructured textual data to recognize patterns, tag data and perform predictive analyses.
Sentiment Analysis
Opinion Mining. Analysis that extracts the subjective opinions or feelings expressed in text, video or audio data.
Image Analytics
Advanced image analysis to extract information, meanings and viewpoints.
Video Analytics
The process of extracting information, meanings and viewpoints from video sequences.
Voice Analytics
The extraction of information through audio recordings of conversations.
Our Services
Advanced Data Analytics
We help our clients to define and implement a data exploitation strategy according to their needs.
- Team with extensive sectoral knowledge.
- Advanced analytics service using the latest data science technologies, tools and techniques.
- Adaptable use cases: fast time to market.
- Application of various disciplines: deep learning, machine learning, AI, predictive and recommender systems, natural language processing (NLP), etc.
- Data extraction, cleansing and analysis; algorithm definition and design; business communication.
- Productization of developments.
Strategic Consulting& Business Intelligence
We use strategies based on data-driven models to characterize and predict scenarios, focusing on the optimization of business processes.
- Optimization of business processes.
- Attainment of business intelligence plans.
- Data visualization.
- Dashboard systems.
Behavioural Targeting
We identify patterns and behavioral tendencies to predict different aspects of future behavior.
- Personalization of interactions based on preferences.
- Personalized promotional campaigns according to needs, habits and tastes.
- Loyalty initiatives to prevent potential losses.
- Predictions of non-payment.
Social Perceptions
Conversion of comments, mentions and opinions shared through open sources (social media, web pages, blogs, forums, etc.) in order to determine the social perception of the brand.
Data Visualization
Visualization that helps to interpret information in context through reports, infographics, dynamic maps, real-time dashboards, etc.
