Our big data engineering services allow you to innovate, experiment with new tools, explore new ways of leveraging data, and continuously optimize your big data solutions.
Traditional warehouses were never designed to handle the growing volume, variety, and velocity of Big Data. As new business practices require bigger and fresher data, you might have already thought about modernization of your Data Warehouse to keep it competitive, growing, and aligned with new business and technology requirements.
Most Data Warehouses have room for improvement. Our team of world-class data engineers will help you accommodate massive data volumes, new data types, and new data processing workloads by adding data platforms and analytics tools to your Data Warehouse environment.
We can also help you with legacy system retirement, replacing traditional Data Warehouse with a modern one optimized for today’s requirements in big data, analytics, real-time operation, high-performance, and cost control.
Technical success depends on the team – our team can bring years of experience with big data engineering and analytics to your company, and ensure success of your Data Warehouse Modernization project.
To capture and get business value from new types of data you need to constantly develop your data storage, management, and analytics capabilities. The immediate modernization opportunity for many organizations lies in establishing a Data Lake.
Our experienced engineers will ensure that your Data Lake is delivered on budget and time, has scale and analytics processing power that you need.
Whether you want to analyze immense volumes of data recurrently or ingest and process streaming data in real time our data engineers will help you create a big data processing system tailored to your business requirements.
Batch processing is the right approach for high-volume, repetitive, non-interactive business tasks. But more often you need to analyze rapidly changing, multi-structured data in real time. Our big data engineering services will help you build the business-critical applications that can process large streams of live data and provide results in near-real-time.
We use open source technologies like Spark, Hadoop, Flink to enable advanced analytics and the real-time use cases that are driving business innovation.
Big Data applications deployment might be a challenging task as well. We help our customers to deploy their Big Data applications anywhere they choose: on-premise or in the cloud.
|Data analysis & platforms||MapReduce, Hadoop, Cloudera, HortonWorks, Spark|
|Tools||Lucene, Solr, ElasticSearch, Apache Mahout, Apache Kafka, Apache Pig, Splunk|
|Databases/Data warehousing systems||MySQL, Oracle, MS SQL Server, Redis Couchbase, HBase, Cassandra, MongoDB, Hive, Neo4J, Aerospike|
|Business Intelligence||Pentaho, Superset|
|Programming Languages||R, Python, Java, Scala|
|Visualization||SAS VA, Tableau|