Data comes to life when powerful engineering is combined with analytics. Integrating reliable, scalable, and repeatable practices into your data platform is crucial for analytics and data-driven business decisions.
Leverage your data to the hilt. Apply science and the latest tools and technologies to get the most from one of your most precious resources: your data.
Consulting with customers in architecting a successful data lake that is flexible enough to accept multiple data sources, volumes, and data types all while being able to scale with your business is harder.
We enable the advantage of cloud-based data lakes as compared to “legacy” big data storage by decoupling storage from compute, enabling independent scaling of each. For these requirements, object-based stores have become the de facto choice for core data lake storage in cloud architectures like AWS, Google and Azure which offer object storage technologies.
Our ConvergDB is open source software that creates and manages serverless data lakes with a DevOps friendly workflow. Users describe the structure and behavior of their data, then ConvergDB creates the infrastructure and scripts to do the heavy lifting of optimization and transformation. We leverage cloud services such as Amazon Glue, Amazon Athena, Amazon Redshift Spectrum.
We enable transition from using a single data warehousing technology, opening you up to the portfolio of analytics tools provided by AWS. AWS continues to add new analytic tools to its portfolio which can be quickly deployed in the cloud environment.
ConvergDB automatically batches large data sets which is ideal for the initial conversion of historical data and allows for better management
We design a single store architecture for all data in the enterprise ranging from raw data to transformed data managed on the top-tier cloud service providers and EON mode on AWS. The data lake infrastructure is managed in a single configuration file.
With our tools and expertise, we automate the extraction of source data from a JDBC compatible relational database. We analyze the ETL jobs and categorize them depending on the complexity of the jobs. We leverage a conversion tool to automate the conversion of the jobs. We continue with a focus on job design and performance tuning and ending with acceptance testing and ensure all functionalities and performance criteria are met.
We support identification or creation of real world SQL queries that test the Data Lake performance and assist in evaluating the impact to reduction in TCO.
As your company captures large volumes of data, you need a trusted partner to help you transform those numbers into actionable information. Beyond soft’s team of business intelligence and ETL experts will not only help you analyze and process your data, but also enable you to identify statistical indicators to help you make better decisions. Our in-depth and cost-effective approach takes a look at your business from the top down while looking at your data from the bottom up to turn data into decisions, decisions into actions, and actions into results.
