Big Data Services
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In today’s digital economy, data is an organization’s most valuable asset. Whether enhancing products, improving operations or understanding buyer behavior, monetizing that data is key to driving positive business outcomes. We help you go beyond your data to enable real-time, predictive analytics that will drive your business forward. By assessing your current analytics maturity level and creating a roadmap for execution, we can build the right objectives, deliver on execution, and evolve your organization towards an analytics center of excellence.
Our Big Data offerings:
Click the service titles below to read more about each offering.
HIGH PERFORMANCE CAPABILITIES:
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 of 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.
DATA MODEL AND ETL CONVERSION:
With our tools and expertise, we automate the extraction 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.
QUERY PERFORMANCE-BASED TCO ANALYSIS:
We support for identification or creation 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. Beyondsoft’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.
What our customers expect:
Analysis & Reporting
With so many marketing analytics technologies available today, our mission is to remain tool agnostic while building a marketing technology stack that will be the best fit for your organization. We ensure that your data stream can reside on a robust platform and can be activated for consumption.
- Global 24×7 Support
- Cloud Agnostic
- Elite team of data artchitects
- Open source / IP accelerator tools
- Extensive Partner network
How DataOps Unleashes Data Analytics
Despite the rush to embrace innovation, enterprise data programs’ success is often lackluster due to data liabilities, including anything that impedes the inability to manage data from source to consumption at the speed, scale, and efficiency. But as corporations increasingly embrace data as a key asset, building an organization’s data and analytics competency is key.
In this report, we explore:
- Why high quality, reliable data is critical to the future of your business.
- The top issues impeding data analytics programs, including data liabilities.
- The importance of DataOps and how this framework solves the data liabilities challenge.
- Critical eps for addressing your data liabilities challenge with DataOps.
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