Data modernization & Big data

Modernization, Architecture, Migration and 24/7 Managed Services of modern Data and Big Data platforms.

Turn your raw data into Relevant information (big data)

Axis is an agency specializing in massive data. Take complete control of your company's data with customized information flows. We collect, segment, and unify data in batches to provide you with relevant information. In addition, we automate information actions so you can make predictions about your business with great agility and speed. Our data engineers have the expertise and knowledge to drive data platform projects across all industries. Our Data Platform in Azure has already been implemented at more than a dozen clients.

Digital transformation: A cultural revolution for companies

Axis allows companies to better control their data stock in order to extract relevant information to manage the challenges inherent to Big Data more efficiently. This is why our data management agency uses high-performance technological tools to collect relevant data for you and implement a strategy marketing Our Big Data strategy experts have a real data collection strategy in place to get the right data to help your online growth and deployment.


The accelerated growth of the Internet has led to the proliferation of a large volume of data that allows companies to access a wide range of information about their customers and prospects. Axis is an expert in Big Data, in order to carry out well-targeted marketing campaigns, the company carefully and thoroughly analyzes all the data it collects and builds a well-established Big Data strategy.

Data modernization - Big data - Axis data modernization agency and Big data better

Big Data allows access to colossal databases in real time and is often explained by these 3Vs:

01

Volume : refers to the processing of the very large volume of data (terabytes and petabytes) generated every second from many different sources.

02

Velocity: corresponds to the speed of data analysis in real time (a fraction of a second), but also to the speed of data creation and the speed of data flow.

03

Variety: analysis of heterogeneous data (all types of formats). It is structured data (precise information located in a fixed field and in a predetermined format allowing machines to interpret and process it).

Analyse Big data - modernisation des données - agence big data - Axis

Data Analytics : Data analysis Big Data

There are four main types of data analysis: diagnostic, descriptive, predictive and prescriptive. Data analytics optimizes the efficiency of many industries with different priorities.
The financial services industry uses data analytics to predict market trends and assess risk. Credit scores are one example of data analytics that uses multiple data points to determine loan risk. Data analytics is also used to detect and prevent fraud to reduce the risk to financial institutions. In other industries, data analytics can provide information to crime prevention and environmental protection, critical information for healthcare. Big data and advanced analytics techniques can detect patterns in complex systems.

Data Analytics : Data analysis Big Data

There are four main types of data analysis: diagnostic, descriptive, predictive and prescriptive. Data analytics optimizes the efficiency of many industries with different priorities.
The financial services industry uses data analytics to predict market trends and assess risk. Credit scores are one example of data analytics that uses multiple data points to determine loan risk. Data analytics is also used to detect and prevent fraud to reduce the risk to financial institutions. In other industries, data analytics can provide information to crime prevention and environmental protection, critical information for healthcare. Big data and advanced analytics techniques can detect patterns in complex systems.

Analyse Big data - modernisation des données - agence big data - Axis

Data Governance

It is critical to have data governance in place for these reasons:

  • To optimize your operations: Ensure your data is relevant and of high quality to make informed decisions.
  • Control storage expenses: Process and categorize your data by usage and lifecycle to streamline your storage costs.
  • To secure your data: Secure your confidential data and your customers' data to protect your turnover and your brand image.
  • Accelerate innovation: Get ahead of your competitors by using the right data at the right time.
  • To save time: Collect, store and feed your data analytics in real time.

Data visualization solution

Data visualization to better exploit its value
Data Visualization in general consists in representing data in the form of graphic to make it easier to understand. Users (people) without extensive technical knowledge can visualize, analyze and communicate efficiently and independently with the data.
After being collected, processed and modeled, the data is formatted to facilitate the identification of patterns, trends or outliers. Combined with a data model prepared for analysis, Data Visualization tools and techniques allow you to leverage your KPIs (key performance indicators) to quickly make strategic decisions for your business.

Data visualisation modernisation des donnees agence big data

Fair for Questions

What is Big Data?
Definition that comes closest to Big Data
Big Data or megadata refers to all digital data produced by the use of new technologies for personal or professional purposes. This includes corporate data (emails, documents, databases, business processors history...) as well as data from sensors, content published on the web (images, videos, sounds, texts), e-commerce transactions, exchanges on social networks, data transmitted by connected objects (electronic tags, smart meters, smartphones...), geolocated data, etc.
What are the main components of Big Data ?
Big Data
The components of a Big Data architecture are: Storage (data warehouse, data lake) Data source (data mart, data warehouse, cloud, hybrid database) Batch processing Stream processing (data flow processing); Data preparation; Data catalog; Data modeling.
What is Data visualization (Dataviz)?
Data Visualization
Data visualization or dataviz is a discipline of data science that uses graphical tools to translate large amounts of data into understandable visuals. It makes the collected data intelligible in order to transmit information via representations accessible to all.
What is the purpose of dataviz?
Importance of data visualization
Dataviz is a tool that allows you to decipher information contained in a large data set, used to determine influential trends in an industry.
What is Big Data used for?
It is essential
In all sectors, companies and organizations use the Big Data stored in their systems for different purposes. It may be primarily to improve operations, it may also be to provide better customer service, and to create personalized marketing campaigns based on consumer preferences, or even simply to increase revenue.