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⚒    Intro     Why Bi&A (I)     Why Bi&A (II)     BI_proces     ANA_proces     What next     ⚒ 👐    top bottom   👐

Design BiAnl- Business Intelligence - Analytics


Improving processes - change transitions

Explaining - predicting, processing operations.

BI life work cell Data BI technology The world of BI and Analytics is challenging.
The Application Life Cycle model2 is underpinning decisions for in the boardroom. To know what is going on and what is needed, distance on details is required.

🔰 Most logical back reference.

Contents

Reference Topic Squad
Intro Explaining - predicting, processing operations. 01.01
Why Bi&A (I) Why BI & Analytics (I). 02.01
Why Bi&A (II) Why BI & Analytics (II). 03.01
BI_proces Business Intelligence Proces. 04.01
ANA_proces Analytical Proces. 05.01
What next Inventing changing Operations. 06.00
Combined pages as single topic. 06.02

Combined links
Combined pages as single topic.
👓 info types different types of information
👓 Value Stream of the information product
👓 transform information Working cell
🚧 bi tech Business Intelligence, Analytics
🕶 data for BI analytics reporting

Progress

THis chapter is partially fresh, partially converted. Topics are:
dual feeling

Why BI & Analytics (I).


Informing the decision makers (business).
Supporting Business proces optimization.
Business Intelligence (BI), Management Information System (MIS), Executive Information System (EIS) are alle the same, just using different words.
The goal is only informing management with figures so they can make their mind up with what do in the future.
The spreadsheet use by mangement doing the analyses for decisions.

At other layers "BI & analytics" is used: BI & Analytics is not a "one size fits all" solution.

Informing by descriptive reporting.
In the years before BI was normal, the standard reports were delivered as being part of the proces job log. The reports being printed on paper were archived for a long period, requiring a lot of space and cabinets.

Extracting those numbers, figures, was later done by archiving those prints in an electronic way (datasets). The conversion of those electronic datasets was the first dwh being build. The spreadsheet being a key enabler replacing most of manual work.
Why Business Intelligence
📚 short list:
* standard
* ad hoc
* drill down
* alerts


Bi as the next thing of report log

First BI&A usage:
  1. Moving the evaluation log to BI tools
    Every Job did have an associated rprot printed what has happend.
    The change into collection of those reports into:
    📚 " Intelligence".

dual feeling

Why BI & Analytics (II).


Informing by predictive, prescriptive reporting.
Analytics, Operations Research (BI) is coming wiht a lot of uncertainties. Monte Carlo simulations being optional.

This is augmenting reporting, doing extrapolations, regresions in probablities what could happen.
Why Analytics, Machine Learning
short list:
* statistics
* forecasting
* predictions
* optimizations


Analytics and Bi differences

Different type of BI&A usage:
  1. Operations using BI tools
    No preparation on what is needed neither evaluation what has done.
    Focus: running the operations.

  2. BI, Business Intelligence (dashboard-report)
    📚 Information is being gathered wiht a discussed goal to achieve.
    ⚙ ⚒ Data is being processed. Prepare for the goal.
    🎭 Results are evaluated, planning what do next.

  3. AI, BI enhanced with analytical tools (dashboard-report)
    ⚖ ⚙ Information is being gathered having no clear goal to achieve.
    📚 ⚒ Modelling - analyzing using data, to find new unknown opportunities.
    🎭 Results are evaluated, planning what do next.

  4. AI, ML Machine Learning, operational scoring
    ⚖ ⚙ Information is being gathered with a discussed goal to achieve.
    📚 ⚒ Modeling - analyzing data for the best approach.
    🎭 Results associated wiht tested models are evaluated.
    Data is processed using accepted chosen models.

 legal

Business Intelligence Proces.

The classic approach is delivering just reports dashboards.
The historical connotion is that a dwh DataWareHouse has an 1-1 association wiht this approach.

ALC model2 BI&A.
Business Intelligence Proces
In this infographic flow:
handy tool
Using Bi-tools
💣 The tools originally reserved for BI only use have become far more generic. With the type of BI&A usage there is already a list of four different type of users a "datawarehouse" - "data lake" should able to provide.

 legal

Analytical Proces

Automatization of decisions within predefined settings and predefined limits of variation. Any automated decision has to be explainable and able to possible be correct by human intervention. (profiling GDPR)

ALC model3 BI&A.
analytics proces
In this infographic flow:
handy tool

Inventing changing Operations.

💣 Analysing data is requiring real operational production data. Building decisons on faked information would generate very wrong results. Whether it is basic analytics doing reporting or automatized ML it is =level 3= (orange).

EMC - Big Data infographic (2013)
A nice review on this, "The big data journey rivisited" Bill Schmarzo 2016.
emc big data storymap


Combined pages as single topic.
Combined links
👓 info types different types of information
👓 Value Stream of the inforamtion product
👓 transform information Working cell
bi tech Business Intelligence, Analytics
🕶


🔰 Most logical back reference.



⚒    Intro     Why Bi&A (I)     Why Bi&A (II)     BI_proces     ANA_proces     What next     ⚒ 👐    top bottom   👐
📚    BPM    SDLC    BIAanl    Data    Meta    Math    📚 👐 🎭 index - references    elucidation    metier 🎭

© 2012,2019 J.A.Karman