Data Science

Data Modeling

Comprehensive ‘data sets’ with distinctly chosen ‘elements’ and ‘variables’ have helped us advise stakeholders in choosing and applying techniques corresponding their needs (categorical vs numerical), dealing with all give data types i.e., nominal, ordinal, interval & ratio.

Descriptive Statistics

Let’s get to know how your business data provide you with basics of analytics. You may have already thought whom is your most attracted audience out there just as a kick-start flare. On the contrary, one may be dazzled spontaneous sway of behaviour by a certain client. Set fundamentals of your databases in order to generate such trivial information for your venture.

Sampling & Sampling Distributions

Random selection on regular basis, like how we control quality in Manufacturing, is in fact observatory evidence for decision making. Making sure randomness is fulfilled by following certain ‘sampling’ rules, we will be able to use attributes of each sample for calculation of probabilities in large populations. If you are interested to discuss how we’ve been using this in different Sectors, please don’t hesitate to Contact Buildpath.

Interval & Point Estimation in Sampling

First move is to drive the customer towards a solid state of Empirical Rule in analytics. Business helps clients in accumulation of samples in hefty sizes containing well defined criteria that will make management teams to run various in-depth comparisons using principles of statistics and probabilities. This has assisted firms in generation of different types of probability distributions (continuous and discrete) ultimately instituting such estimating techniques within decision making process.

Hypothesis Analysis

Every idea that springs to mind is a hypothesis. But is this going to become popular? Probability of such is not for anticipation but rather mere calculation of a point on a Normal Distribution and explaining how this would help your business or your decision-making process. Your data distinctively proves it right or wrong by choosing right ‘data model’.


Probability Distributions

Our final advice to businesses in terms of ‘data analytics’ would be to correlate your chosen sample group to right function hence distribution. That depends on nature of criteria, variable type and obviously what client is interested to know. Your analysis will be inevitably based upon either a ‘discrete’ or a ‘continuous’ distribution and that particularly defines applicable algorithms. Contact us to discuss different circumstances where these techniques have been implemented in a number of Industries and see how this adds value to your business.

Risk Management

Company’s portfolio of liabilities has proved the management team that their sampling and statistical modelling is in line with right indices of Risk Management. Contact Buildpath to discuss how techniques such as Monte Carlo, that is evident manifesto for importance of Data Science in enterprise management, can be applied and help you in a number of industry Sectors. Under Production Management frameworks or Project Management, we rely on most common techniques and foresight to establish perceivable analogical approach to the chosen random variable indicative in your decision-making processes.

 

TAKE A LOOK AT THE INDUSTRIES WHERE THESE SERVICES HAVE BEEN MANIFESTED

 

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