Big Data & BI

Manage and make sense of all sorts and sizes of data, big or not.


It’s not just about massive amounts of data. It encompasses a set of powerful open source tools that help to manage and make sense of all sorts and sizes of data, big or not. The first step is to understand these new technologies, the new way of thinking – and how it can help you. M&S will partner with you to identify high-ROI use cases and develop a practical plan.

  • Develop an Enterprise Big Data Strategy
  • Understand the Internet of Things
  • Perform a Big Data Applicability Assessment
  • Provide Mentoring, Best Practices and Knowledge Transfer
  • Develop a Roadmap from Traditional BI to Big Data

Data Science

Data Science applies the mathematical discipline of analytics and predictive modeling to cut through confusion and uninformed opinion. Our Data Scientists will work with you to understand your problems and goals. With precision and practicality, we will create and implement an affordable, achievable system for you to take advantage of Big Data technologies quickly and with high ROI.

Machine Learning (ML)

Algorithms are the lifeblood of machine learning – and machine learning is at the heart of Big Data. But it isn’t magic. ML techniques must be applied with caution and discrimination. In the hands of the uninformed or inexperienced, ML can lead to invalid and misleading results.

Our experienced Data Scientists will use their maturity and experience to guide you through –

  • Predictive Modeling
  • Data Mining
  • Clustering, Linear Models, Support Vector Machines, k-Means, KNN, and other algorithms

Enterprise Data Warehouse

You don’t have to have big data in order to benefit from Big Data tools. There are great open source tools which can fit smoothly into your existing data warehouse environment. Hadoop can relieve the nightly batch processing without having to invest in additional expensive RDBMS licenses or hardware.

Use Hadoop to:

  • Pre-Process Data for loading into the EDW
  • Pre-Aggregate Data for use in BI applications
  • Act as an inexpensive landing zone for raw data sets
  • Provide an inexpensive, redundant data repository

Data Lakes

They’ve been called data lakes – and data swamps. The truth is they are powerful data repository tools which can turn into swamps if not designed and managed properly. Don’t make the mistake of jumping in without a plan. Implementing best practices from the beginning can help you get real value out of a data lake.

We will lead you through the design and implementation using simple but powerful techniques like landing zones, cataloging, data lineage and unstructured data pre-processing.

Data Mining & Analytics

Go beyond the row and column sums you’re getting in your typical BI applications. Data mining techniques can help you deepen your insight and test your assumptions. Produce actionable metrics which enable your decision makers to make informed choices based on facts and sound analysis – not guesses and gut instinct.


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