Database solutions
Relational databases:
The elements in a relational database are organized into tables, with rows and columns. They are the right choice for cases where data integrity is very important (ACID compliant).
Examples: MySQL, Microsoft SQL Server, PostgreSQL, Oracle
Non-relational databases:
They are an alternative to relational ones as web applications have become more and more complex. They are agnostic in terms of the scheme used, allowing unstructured or semi-structured data to be stored and manipulated.
● Key-Value Stores: Redis, Amazon DynamoDB
● Wide-Column: Cassandra, Apache HBase
● Document Stores: MongoDB, Couchbase
● Graph Databases: Neo4j
RDBMS management
Ensuring data integrity
NoSQL fast data stores
Modelling and normalization
Data backup & syncronization
Query plan & optimizations
Business intelligence and data analysis
Data analysis is essential. Statistical algorithms find correlations, hidden patterns or trends, used to make better-informed decisions.
Sphinx, Elasticsearch
Google Data Studio
Apache Spark
Data aggregation
Visualization and charts
Trends and prediction systems
Services for big data
Management of very large volumes of data, both structured and unstructured, over 10 TB. They have enormous potential in discovering important information for your business, can improve decision making and create competitive advantage.
● Big Data Storage: data storage in the cloud is done in a secure, accessible and easy to use way. Several platforms can be used, depending on your needs: Hadoop, MongoDB
● Data mining: data extraction using mathematical and statistical methods (cluster analysis, anomaly detection, sequential pattern mining, association rule mining): KNIME, RapidMiner
● Data Analysis: Data analysis in order to obtain the necessary information in the decision process : Apache Spark, Presto, Tableau
● Data Visualisation: The best way to present data is to turn it into charts, presentations, and tables : Plotly, DataHero, Google Data Studio, ChartJS
Horizontal scaling
Map & reduce algorythms
Data redundancy
NoSQL query rewriting
API and data ingestion
SQL-NoSQL data transfer
API integration and automation
We use the available APIs or build our own APIs for ingesting and serving data, semantic content, and media between entities. OPTI uses the best practices and ensures that the API remains as flexible and extendable as possible
Cloud infrastructure
Amazon Web Services, Google Cloud Services, Azure
Custom APIs
Zapier, Salesforce, Hubspot, Azure, Google API
Analytics and tracking
Google Analytics, Piwik, Semrush
Relational Databases
MySQL, MariaDB, PostgreSQL, SQL Server, Oracle
Non-relational Databases
MongoDB, Redis, Cassandra, Firebase, Hadoop, Google BigQuery
Testimonials
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