Strategic advice

We are specialists in matching you with the right solutions.

Custom solutions

We build and customize solutions to fit your business needs.

Agile governance

We ensure that the Business-IT-alignment performs optimally.

Eco-conscious

We are a long way to go, but are on the right track to improve.

Spot

Let us make the journey easier. We tap into the building blocks of your organisation and deliver you a competitive edge.

Data

What do we collect through observation? Data are a set of values of qualitative or quantitative variables about one or more entities or objects. It can be transformed into information and in turn into knowledge.

Technology

What is the critical component of our value system? Technology is the primary delivery route for virtually all value in a modern organization. All services are now, to some degree, enabled by technology.

Process

What do we do in order to deliver the expected value to our customers? Processes are, by definition, repeatable. They will produce the same result every time, regardless of who is carrying them out.

People

What is the most important thing in the world? It is people, it is people, it is people. Without people and the organizations they form, you have no service.

Solve

We operate at the intersection of data, technology, process and people to solve organisational puzzles.

Operational

Descriptive analytics for managing day to day business smoothly with a few action steps on a daily basis.

Tactical

Diagnostic analytics for achieving long range goals with many action steps within months or quarters.

Strategic

Predictive analytics for examining and steering the course of the business with milestones in years or decades to come.

Business Intelligence and Business Analytics as part of Data Science

Business Intelligence (BI) is needed to run the business on the course. Business Analytics (BA) is needed to change the course of the business. BI is looking in the rearview mirror, while BA is looking in front to see what is going to happen and how to make it happen.

Descriptive analytics

What happened? First member of BI and hindsight in nature. It is characterized by traditional BI and visualizations such as pie charts, bar charts, line graphs, tables, or generated narratives.

Diagnostic analytics

Why did it happen? Second member of BI and insight in nature. It is characterized by techniques such as drill-down, data discovery, data mining and correlations.

Predictive analytics

What will happen? First member of BA and one foresight in nature. It is characterized by techniques such as regression analysis, forecasting, multivariate statistics, pattern matching, predictive modeling, and forecasting.

Prescriptive analytics

How to make it happen! Second member of BA and many foresights in nature - a manyfold of Predictive analytics. It is characterized by techniques such as graph analysis, discrete event simulations, and heuristics.

Control

Hindsight. Insight. Foresight. To be in Control, you need all THREE.

Hindsight

Past situation

  • Reactive action
  • Operational level
  • Descriptive analytics
  • Process driven
  • Rule based
  • Simple process
  • Resilient system
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Insight

Present situation

  • Reactive action
  • Tactical level
  • Diagnostic analytics
  • Technology driven
  • Skill based
  • Complicated process
  • Stable system
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Foresight

Future situation

  • Proactive action
  • Strategic level
  • Predictive analytics
  • Data driven
  • Knowlegde based
  • Sophisticated process
  • Robust system
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We leverage Big Data technologies with Reinforcement Learning to further develop powerful data science models into the foresight stage.

Every organisation, big or small, is managing a considerable amount of data generated through its various data points and business processes. At times, organisations are able to handle these data using excel sheets, access databases or other similar tools.
However, when data cannot fit into such tools, and human error instances increase above acceptable limits due to intensive manual processing, it is obvious to leverage Big Data technologies.

We operate unsupervised learning on Big Data and its characteristics – Volume, Velocity and Variety - to further develop powerful data science models into the foresight stage.

Data Volume

Amount of data generated
Online and offline storage
Saved in files, records, or tables
In gigabytes or terabytes

Data Velocity

Speed of generating data
Online and offline transactions
Collected as time and/or event based
In streams, batches, or bits

Data Variety

Numerical, text, image, audio, and video
Structured and unstructured data storage
Human generated
Machine generated