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Analytics and Big Data
We have clients who use big data analytic techniques against very large, diverse data sets that include structured, semi structured, and unstructured data from different sources and in different sizes (from terabytes to zettabytes). According to IBM, “Big data is a term applied to data sets whose size or type is beyond the ability of traditional relational databases to capture, manage and process the data with low latency. Big data has one or more of the following characteristics: high volume, high velocity or high variety. Artificial intelligence (AI), mobile, social and the Internet of Things (IoT) are driving data complexity through new forms and sources of data. For example, big data comes from sensors, devices, video/audio, networks, log files, transactional applications, web, and social media — much of it generated in real time and at a very large scale.”
Benefits of Big Data
- Detect and mitigate fraud
- Improve customer integrations
- Drive supply chain efficiencies
- Unified Governance and Integration
- Data Science and Analytics
Our team has expert knowledge in the use of the following big data and analytical software:
- Python
- IBM Analytics and IBM Cognos
- Apache Hadoop
- Apache Spark
- Zoho Analytics
- R
- Qlik Sense
- Micro Strategy Enterprise Analytics
- Tableau
- Google Analytics
- Good Data
Our team, which includes MBAs, Programmers, System and Software Engineers, and Statisticians, have these skills and credentials:
- Programming
- Data Warehousing
- Computational frameworks
- Quantitative Aptitude and Statistics
- Business Knowledge
- IBM Certified Data Architect – Big Data
- IBM Certified Data Engineer – Big Data
- Stanford Data Mining and Applications Graduate Certificate
- Microsoft Certified Solutions Expert (MCSE): Data Management and Analytics
- Amazon Web Services (AWS) Certified Big Data
- Analytics: Optimizing Big Data Certificate
- IBM Data Science Professional Certificate