Big data and data analytics is playing a vital role in making businesses smarter and more efficient. Hence it is difficult to envision a successful business system/app which is not providing insights to its customers. We have developed deep understanding of Big Data and Data Analytics technologies/frameworks and business domains to help you provide critical insights from disparate data sources.
AFour Dev’s Big Data and Data Analytics practice has worked in diverse domains such as Healthcare and Retail. This makes us to quickly connect with the business drivers behind the big data implementations and allows us to help you in the process of use-case discovery, solution design and execution plan/roadmap.
Big Data & Data Analytics Use Cases
Big Data & Analytics (Technology)
We worked in diverse domains such as Healthcare and Retail. This makes us to quickly connect with the business drivers behind the big data implementations and allows us to help you in the process of use-case discovery, solution design and execution plan/roadmap.
Hadoop | MapReduce, HDFS, HBase, Hive Query Language, HCatalog, Storm, Spark, Mahout, Pig, Oozie, Zookeeper, Flume |
NoSQL | MongoDB, CouchDB, REDIS, Cassandra |
Search | ElasticSearch, Solr |
Analytics | Kibana, Intellicus, GoodData |
Distros | AWS Elastic MapReduce, Hortonworks, Cloudera CDH |
Data Science & Analytics
- Creating Insights based on given data, like Trend Analysis, Focus Areas, etc.
- Analyzing and creating Visualizations like Graphs, Plots, etc. based on data
- Predicting Outcome of data by creating different Machine Learning Algorithms, using techniques like Regression, Decision Trees, etc.
- Creating data models and applying various validation measures to check the models before going to Production and also re-verifying the models over time
- Generating pre-learn models from existing data which also provides self updation of models
- Modelling data and creating models to be used for forecasting techniques
- Experience in creating algorithms and models like Churn Propensity, Cross Sell, Time Series type models, etc.