Data analysis

A thorough evaluation of your data reveals innovative insights about your organization, generating business intelligence that sets you apart.

Discuss a project

We help you to maximize your decision-making

Effective decision-making is at the heart of any successful business. By utilizing cutting-edge technologies, precise analytics, and in-depth expertise, we transform your raw data into valuable and actionable insights.

Kashika Studio, our data-focused division, helps you identify hidden opportunities, understand complex trends, and make informed decisions that propel your business forward. Whether it's business strategy, investment, or operations, our mission is to provide you with the clarity and confidence needed to maximize the impact of every decision you make.

Why analyze your data with experts?

Quick results

Our experience accumulated over the years gives us the ability to skillfully handle the most advanced analytical tools, thereby facilitating in-depth and accelerated studies.

Periodic follow-ups

A regular support that helps you achieve your goals while empowering your team to push you to progress further.

Precision and bias correction

We manage to ensure high accuracy in the interpretation of data while striving to minimize biases potentially introduced by human or technological factors.

The steps of a successful data analysis

Definitions of objectives

Identifying clear and measurable objectives allows for directing analytical efforts throughout the process. They can evolve based on discoveries made as new knowledge is acquired.

Specific and Measurable: Objectives should be clear and well-defined, with key metrics to evaluate performance.
Achievable: Objectives are realistic, and you have the necessary resources to achieve them.
Relevant: Objectives should be aligned with the overall mission of your company or organization.
Time-bound: There should be a clear timeline for achieving your objectives to ensure timely progress.

Data collection and cleaning

We collect all of your current data sources to study their structure. This step allows us to understand the extent of the available information. If the latter is of poor quality or insufficient to meet the objectives, a data strategy will be essential before proceeding with the analysis.

Study the structure of current data
Select and clean relevant sources
Set up a data lake to centralize the information to be processed

Iterative analyses

Once the objectives are defined and the data is centralized, our experts can begin their analysis. With fast and flexible processing tools, we quickly identify the most relevant insights to develop appropriate statistical strategies.

Exploratory analyses to identify trends, relationships, and potential anomalies
Data modeling involving the use of statistical models, machine learning, or other methods to forecast trends, make inferences, etc.
Drawing conclusions from the results of the analysis. This could include identifying trends, formulating recommendations, etc.

Communication of results and follow-ups

Periodically, we present the results in a clear and understandable manner. This may also involve creating data visualizations to facilitate understanding.

Data analysis is an iterative process. The results of each analysis can lead to new questions or modifications of objectives, which may require restarting the process.

Presentation of the obtained results
Reevaluation of objectives
Exposure of the limitations of current data (if applicable)
Proposal for additional relevant data collections (if applicable)

Questions and answers

Kashika Studio

Data visualization

info@kashika.studio

(514) 916-3026

Our analyses are meticulously performed by a team of skilled experts who use two of the most powerful programming languages in the industry: Python and R. These tools are recognized for their ability to facilitate the manipulation and analysis of large datasets.

Python, thanks to its robust libraries like Pandas and NumPy, allows our experts to quickly process massive amounts of data. It also offers visualization capabilities through Matplotlib and Seaborn, making the results of the analysis more understandable.

R, on the other hand, is particularly valued for its potential in statistical analysis and predictive modeling. It has a variety of packages such as ggplot2 for data visualization and dplyr for data manipulation.

Together, these tools help our experts to quickly examine data sources, derive accurate statistics, and effectively spot outliers. They enable decision-making based on reliable and relevant information. Their combination provides a comprehensive, precise, and rapid analytical approach, essential for addressing current data challenges.

The scope and duration of analyses can vary significantly, depending on several factors such as your specific objectives, the nature of your questions, and the complexity of the data you have. For example, analyzing data to answer a simple question, such as analyzing sales trends from a single data source, can be done relatively quickly, often in less than a week.

In contrast, if faced with a set of more complex questions that require exploring and correlating multiple sources of heterogeneous data, the time required can extend over several months. These more ambitious analysis projects may involve integrating various datasets, processing unstructured data, applying advanced analytical techniques, and addressing data quality issues.

It is crucial to understand that the time needed to achieve accurate and meaningful results greatly depends on the complexity of the task at hand. That said, our commitment is to provide the most accurate results within the most efficient timelines, regardless of the scope of the analytical challenge.

Data privacy is a top priority for us. We have implemented several mechanisms to ensure the security and confidentiality of the information you entrust to us.

First of all, all data is transmitted via secure and encrypted connections. We also use state-of-the-art firewalls and intrusion detection systems to prevent any unauthorized attempts to access our systems.

The data is stored in highly secure data centers, where physical access is strictly controlled. Moreover, the data is regularly backed up to prevent any potential loss.

In terms of data management, only employees who need access to certain information to perform their jobs have access to it.

Finally, we regularly train our staff on best practices in data privacy and security. We also have rigorous policies in place to ensure that all data is managed appropriately and securely.

We are committed to respecting and protecting the data privacy of our clients at every stage of the process.

The best way to determine if your organization has enough data to meet its objectives is to start by clearly defining those objectives. Then, review your existing data to see if it can meet those goals. For example, if you are looking to understand customer behavior, your data should cover relevant aspects such as transactions, engagement, and returns. If your existing data is insufficient, you will need to consider collecting additional data. A professional assessment by data analysts can also be very helpful.