Data Science

Data Science


tificial Intelligence (AI) which includes Machine learning (ML) and

We typically use a two-dimensional (2D) space or plane or X,Y plot to correlate or associate variables. Moving beyond two can get difficult to understand. Data Science can assist in the database with computations across many records, dimensions, dates and numeric values. Data Science is related to "Computational Statistics" which is the use of computers and statistics.  Alexicon can assist with moving data science code from frontend desktop workbooks to the Enterprise Data Warehouse (EDW) and Data Lake.

Alexicon uses SQL, R, Python and Scala for EDWs and Enterprise Data Lakes (EDLs). Excel, W3Schools, SQL, Python and R examples are used below.

Data science is a "concept to unify statistics, data analysis, informatics, and their related methods" in order to "understand and analyze actual phenomena" with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. - Wikipedia

Simple Linear Regression

Simple Linear Regression is basic and used extensively in Data Science. Below is an Excel and Python (Anaconda Junyper notebook IDE) example.

Below is a chart showing the change over two timeframes (same data - timeframes, lines and computations are stored in the SQL database or backend):

Multiple Regression

Multiple Regression is similar to linear regression and used for prediction by using more than one independent value.

AI applications include advanced web search engines, recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri or Alexa), self-driving cars (e.g. Tesla), and competing at the highest level in strategic game systems (such as chess and Go), As machines become increasingly capable, tasks considered to require "intelligence" are often removed from the definition of AI, a phenomenon known as the AI effect. For instance, optical character recognition is frequently excluded from things considered to be AI, having become a routine technology. - Wikipedia

AI covers many areas. Our data science focus is around Analytics, Predictive Analytics, Forecasts, Root Cause Analysis and Enterprise Optimization.

Machine learning algorithms build a model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed.

Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. This is similar to Machine Learning with Test and Train manually setting categories or automatically creating them working with both data or images.

While typically used in Six Sigma, DOE is a powerful data collection and analysis tool that can be used in a variety of experimental situations. It allows for multiple input factors to be manipulated, determining their effect on a desired output (response). Below an example of data used with DOE.  Minitab is a popular tool for DOE along with R and Python.

Increasing performance requires Process, Analytics and Data Mgmt. (all three working together). Data Science rules or code also exists in all three areas.

To assist with performance gains, Alexicon focuses on the areas below with Process touching all areas:


Align Business Model and Business Processes

Catalog, Forecast, Predict and Score at many levels, increases top-line accuracy

Applications and Analytics provide the workflow intelligence to improve

Measure dollars, quantities and time

Coordinated Processes with Analytics

Use Data Science to Forecast, Predict and Categorize


Optimal Business Processes defined

Enterprise Processes and Systems (ERP and many others)

Measure Processing Time and Wait time

Time intelligence speeds operations and provides clear communication with Associates, Customers, Partners and Suppliers

Gain the process advantage and include learning in the EDW and Data Lake


Visualizations, Dashboards and Reports

Accurate Projections, Prediction and Categorization

Utilize Augmented Analytics

Data Mgmt.

EDW and Data Lake (Single Source of Truth)

Leverage Desktop Excel, SQL, R, Python and Scala code at scale

Query speed and accuracy

Contact us to learn more about accelerating your Company's Data Science efforts with your EDW and Data Lake.