Advancements in data collection tools leading data to now arrive in larger quantities, at a faster pace, and in diverse formats. XilanAI specializes in creating data pipelines for extracting data from various relational and non-relational databases and conducting various ETL (Extract, Transform, Load) operations. Our experts leverage commonly used software solutions and analytic tools such as PowerBI and Tableau to extract valuable business insights and create Dashboards to cater to the unique requirements of our clients.
XilanAI utilizes Hadoop Ecosystem for storing and processing data.
Hadoop Distributed File System module allows distributed storage of massive datasets across nodes in a cluster increasing fault tolerance and resilience.
Map Reduce in Hadoop offers a distributed algorithm for processing and filtering data in parallel on different nodes in a cluster reducing the processing time.
Hadoop Big Data Graph generate and manipulate data by representing and storing information within graphs using nodes, edges, and properties.
Perform data processing through batch and real-time streaming approaches, utilizing your preferred programming language.
Conduct Exploratory Data Analysis (EDA) on data at the petabyte scale without the need to resort to down sampling.
Train machine learning algorithms on a laptop and scale the same code to fault-tolerant clusters comprising thousands of machines.
XilanAI offers scalable solutions for managing large datasets by leveraging technologies such as Hadoop and Spark. This empowers businesses to effectively handle data without concerns about storage limitations.
XilanAI's data solutions are individually tailored to address the distinct needs of every client. This ensures businesses receive customized reports aligned with their precise requirements, leading to increased effectiveness.
Our services incorporate cutting-edge analytical methods and tools to extract valuable insights from data for business use. This empowers businesses to make informed decisions and maintain a competitive edge.