About PROQNOSTIX

Welcome to PROQNOSTIX!

PROQNOSTIX is a side project of the female expert network

https://www.ask-a-woman.com

What does the “q” and the “x” stand for in “PROQNOSTIX”?
“Q” stands for “open source query” and “x” stands for “cross-platform extension”. More about “q” and “x” can be read here

The service portfolio of PROQNOSTIX can be divided into three areas:

I) Know-how development in companies in mathematics

PROQNOSTIX contributes to the integration and development of

  • mathematical knowhow
  • prognosis, prediction and forecasting procedures as well and
  • artificial intelligence (AI) based method.

in your company

In addition to the knowledge transfer, the use and implementation of tailor-made software solutions are also part of the offer:

II) Software Development Procedures for Forecasting and Artificial Intelligence (AI) -based applications

PROQNOSTIX empowers companies to apply prognosis, predictions, forecasts, estimates, and AI-based methods to big data, in light of their business goals. In addition to cloud-based distributable and scalable software solutions, such as Amazon AWS, Microsoft Azure, Google.AI, etc., PROQNOSTIX also employs bespoke software solutions to get the most out of your business based on the latest scientific research and market experience in data science.

III) Emerging Technologies

PROQNOSTIX also creates a forecast report of future potential, from the perspective of emerging technologies, such as Blockchain, Internet of Things (IoT), Serverless Computing, Bots, etc., with the goal of providing meaningful uses for your business and identify and unleash further potential.

Here you can book our workshop:

Prognosis

Prognosis = a forecast of the future course, or outcome, of a situation; a prediction ” (Daigle 2014, p. 7) “

“Prognostics is the ability to predict future events, conditional on anticipated usage and environmental conditions, significantly contributes to a system’s resilience for safe and efficient operation.” (Sankararaman/Abhinav/Goebel 2014, p. 533) “(…)

To prognosticate is “to foretell from signs or symptoms: predict” (Merriam Webster Dictionary 2019)

Prediction and Forecasting

“Prediction is concerned with estimating the outcomes for unseen data. (…) you fit a model to a training data set, which results in an estimator f^(x) that can make predictions for new samples x.” (Döring 2018)

“Forecasting is a sub-discipline of prediction in which we are making predictions about the future, on the basis of time-series data.” (Döring 2018)

Here you can book our workshop:

 

 

References

Daigle, Matthew (2014): Model-based prognostics. Prognostics center of excellence. Intelligent systems division. Nasa ames research center.

Https://www.Phmsociety.Org/sites/phmsociety.Org/files/daigle-modelbasedprognostics-tutorial-phm2014_1.Pdf

Döring, Matthias (2018): prediction vs forecasting. Predictions do not always concern the future … https://www.Datascienceblog.Net/post/machine-learning/forecasting_vs_prediction/

Merriam Webster Dictionary (2019): Progosticate. Http://www.Merriam-webster.Com/dictionary/prognosticate

Sankararaman, Shankar ; Abhinav, Saxena ; Goebel, Kai G (2014): Are current prognostic performance evaluation practices sufficient and meaningful? Annual conference of the prognostics and health management society 2014. Nasa ames research center, Moffett field, ca 94035, USA

DevOps and Big Data

In the era of big data and big code numerous open source tools, libraries, frameworks and code repositories allow IT experts to follow the DevOps approach, where time consuming developing tasks such as deployment, installation, configuration and the set up are automatized.

“Big Code” and open-source Tools

Code repositories offer pre-built, refactorable and reusable working examples for the easy usage within the enterprise architecture. A large set of standardized models, methods, techniques and practices allow developers and testers to perform mathematical operations and analysis such as forecasting and AI with an ease on large amounts of data. The magic lies in the huge number of free usable open source tools and libraries with to access to the APIs of numerous providers of data and code.

Predictive Analytics

PROQNOSTIX enables companies to perform analysis on data, driven by a business goal to predict future developments based on the data, most appropriate regarding the business goals from the perspective of predictive analytics.

Discipline of Econometrics

Thus PROQNOSTIX offers products and services in the discipline of econometrics, defined as “the forecasting of macroeconomic variables, such as interest rates, inflation rates, gross domestic product (GDP) and a collection of methods for the forecasting of economic time series and the prediction of economic theories.” (cf. Wooldridge 2009, p. 1f)

Data can be structured as time series or as cross-sectionnal data.

Time Series Data

Time series data consist of observations on stock prices, money supply, consumer price index, annual homecide rates, automobile sales etc. (cf. Wooldridge 2009, p. 8)

Cross-sectional Data

“Cross-sectional data consists of a sample of individuals, households, firms, cities, states, countries, or a variety of other units, taken at a given point in time. Sometimes, the data on all units do not correspond to precisely the same time period. For example, several families may be surveyed during different weeks within a year, In a pure cross-sectional analysis, we would ignore any minor timing differences in collecting the data. If a set of families was surveyed during different weeks of the same year, we would still view this as a cross-sectional data set.” (cf. Wooldridge 2009, p. 5)

Here you can book our workshop:

 

 

References

Wooldridge, Jeffrey, M. (2009): Introductory Econometrics. A modern approach. South-Western. Cengage Learning. Fourth Edition.

The Art of Forecasts and Predictions

The arts of forecasting is the determination of the best fitting model with the most adequate parameters for a given business goal. There is a large set of models in AI and further emerging technologies, such as blockchain, IoT, serverless computing etc. to be discovered.

Modeling Forecasts

All models will perform differently depending on which application domain they are applied to. The job of the forecaster is to compare those models most suitable for a given issue and to optimize the parameters of the model. The next figure shows an hierarchical overview of widely used forecasting methods and the underlying taxonomy (see Fig. 1):

Industrial Branches

Potentially each industrial branch is affected by the potential for competitiveness. We now focus on three branches in order to demonstrate the potential of the application of products and services of PROQNOSTIX:

  • Banking Industry:
    • Forecastings for investments in the stock markets
    • Forecastings of the creditworthiness
  • Geodata
    • Real estate prices
    • Demographics
    • etc.
  • Marketing
    • Search Engine Optimization
    • Social Media Analysis
    • etc.

Here you can book our workshop:

How PROQNOSTIX proceeds with nubank.de

Nubank.de is a side project of ask-a-woman.com (AAW). Nubank.de typifies a model bank on the basis of a scientific research conducted by experts of AAW. In this research project

  1. PROQNOSTIX supports the definition of the companies business goals cooperating with the domain experts of nubank.de. The evaluation of the potential of big data repositories for the application of mathematical and AI-based methods and practices e. g. for forecasts performed in an software engineering environment provided by PROQNOSTIX is part of the analysis stage.
  2. Definition of technology stack, methods, libraries, tools, resources, tasks, roles etc.
  3. Agile Data Science (ADS): Project management and software engineering process is based on the ADS approach.
  4. Hybrid design of products and services:
    1. Delivery of a running software environment with a software lifecycle.
    2. Inhouse workshops for the usage of big data, open source software and methods of software engineering and mathematics in companies.

Case Study: nubank.de gives an order

The following procedure model is applied:

I Preanalysis

  • First survey and interviews
  • First suggestions and recommendations:
    • A) Investment strategies on the stock markets based on numerous key performance indicators of companies and feasibility analysis for mathematical methods.
    • B) Calculation of the creditworthiness of private persons and companies based on data (Schufa, Social Media, self-declerations)
    • C) Potential analysis on emerging technologies, such as Blockchain, Serverless Computing, IoT, VR/AR/MR etc.
    • D) Designation of workshop content
  • Milestone: Go?

II Requirement Engineering

III Design

IV Model

V Implementation

VI Test

VII Evolution

WORKSHOPS AND SEMINARS

CONTENT OF THE WORKSHOPS AND SEMINARS

The course content is divided into three parts:

  • I) Application Areas
  • II) Methods, Techniques and Best Practices
  • III) Future Potential of Emerging Technologies

The workshops are bookable in packages of

  • 1 day á 6 hours (Light Package) or
  • 3 days á 6 hours (Full Package)
  • Other offers are available

The price for a workshop is 150€/h plus taxes:

  • Light Package (900€ plus taxes)
  • Full Package (2700€ plus taxes).

I) APPLICATION AREAS

We first give an overview on potential application areas and then focus on the requesting companies branch.

As an example the banking industry is likely to be interested in

  • forecasts for investments in the stock markets and therefore the companies key performance indicators,
  • forecasts of the creditworthiness of a private person or a company,
  • the application of AI methods etc.

The Geo Information Systems (GIS) sector is applying forecasts and other mathematical methods on the development of

  • Real estate prices
  • Demographics
  • etc.


And marketing departments and agencies are interested in the success of their campaigns in the fields of

  • Search Engine Optimization
  • Social Media Analytics
  • etc.

II METHODS, TECHNIQUES & BEST PRACTICES

In the second part of the workshop we address primarily methods, techniques and best practices of Mathematics, Informatics and Business administration, but we´ll also take into account methods from other branches.

Methods, techniques and practices of mathematics are as follows:

  • Statistics
  • Artificial Intelligence, Machine Learning, Deep Learning
  • Libraries & Tools

Informatics

  • Tool Portfolio
  • Software Engineering
  • Modeling
  • Programming Languages

The discipline of Business Administration serves companies with methods such as

  • Project Management,
  • Controlling,
  • Logistics,
  • Sales
  • etc.

Potentially any methods, techniques and best practices of any other discipline or branch, such as law, health sector, entertainment sector, car industry etc. can be listed here.

III FUTURE POTENTIAL OF EMERGING TECHNOLOGIES

The third part of the workshop enlightens the potential of emerging technologies, elaborates and prognosticates opportunities out of the following emerging technologies:

  • The blockchain is obvious to be the technology with the most potential impact on transaction processes of the future. Since transactions are the core of entrepreneurial interactions with the customers and employees, this subject will also be evaluated for the attainment of defined business goals.
  • The Internet of Things (IoT) has growingly significance for the future markets. A prognosis on the potential for the given company will be conducted during the workshop.
  • Bots undertake more and more tasks in the interaction between companies and customers, reducing increasingly costs e. g. in the support departments.
  • Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR) offer new opportunities for the creation of raised user experiences with products and services of companies for private households and industries.
  • Further Emerging Technologies such as 3D- and 4D-printing, Autonomous Vehicles (AV), Drones, Transhumanism etc. will be discussed, too.