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My Stroke, My Life, My Daughter Victoria – Update 2023 – 10 years later, Self Governance for Health

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I don’t want to bother you, however, I’d like to give you some info new to me and a recent surprising discovery.

In no way, I don’t mean this to be TMI however, you should know what you can find out yourself

Health update, 9 years post stroke after losing extreme amount of weight and changing my diet. On June 3, 2014 I had a brain stem stroke(PONS). Apparently I’m still alive

I’ve posted some Of this on Facebook, i’d like to add some more findings, discoveries and changes in my life. Let me say unequivocally there have been two women in my life with me life that are at the center the first my wife, Teresa Krebs and of course, my daughter, Victoria Stasiewicz

My wife Theresa passed several years ago, and I’d have reconciled that event However, since then there has been some fantastic news and surprising in some new challenges. Due to the stroke and my health improvement and, of course, Victoria

In the time I spent with my daughter and son-in-law in their home, my daughter gave a presentation regarding self governance for Health. This would come to be be a turning point in my life

The main premise is that with today’s tools and health devices, we can monitor our health very scientifically and accurately without a doctors intervention, or interpretation The conditions I suffered from were due to the food I ate and my lifestyle, no, DNA. It was not destined to happen I caused them, hence self governance. – Health..

Following Victoria‘s advice and counsel I am in very good health now. I have metabolic readings of it again that took myself, I can see for myself

I have lost over 100 pounds in the last 2 years. I didn’t go on extreme diet I just ate whole natural foods an actual proper human diet ,based on my daughters advice. In addition to that my blood pressure condition and diabetes2 went away, my eyeball shots and everything elsewent away in general. My health has now completely back to normal .

I have embraced her proposal, and would like to outline the results following

In addition when I started 280 pounds almost 300 I had high blood pressure, I had retinopathy in both eyes requiring two shots in each eye every six weeks I had early stage, kidney disease, and all the other medical problems associated

Also, I took several medication every day for these conditions of Cours Dan last two years no medication’s at alli

Along this journey, I’ve also done thousands of hours of research, and like many millions of folks, I have discovered, and proven that Victoria‘s advice was perfect and well thought out

No for “the rest of the story“ I am currently dealing with balance issues and speech issues basically, my brain did a reset because of the drastic changes in my health for the better frankly due to Neuro plasticity, I will recover it is important to realize the doctors will believe my condition is worse that is farthest from the truth, it is much I realize it’s with their training, It is ananomaly my losing weight and regaining health. I even had one doc say it was probably Cachexia – Muscle wasting However, it is not my blood work is fine is that they have not seen this as a result of the stroke rather not a person wanting to improve their health hallucinate

It took me a while to research that, but what is surprising is that they are both good news

Both caused by a conditions,known as stroke decomposition and vestibular dizziness

I suffered a stroke in 2014 right Pons Brain stem stroke my brain adapted with neural plasticity over last 10 years and I adapted to my disabilities, although I was continuing to degrade my health and weight through improper nutrition

Basically, I’ve confused my brain because it was used to that I weighed over 260 pounds. I know weigh 148 pounds. Hence, I have some balance and speech issues due to stroke, decomposition, and Vestaview dizziness

I am writing this, only to let people know that our current medical professionals are not equipped to treat us. Losing this much weight while, surviving from a stroke has it complications

This is not me getting worse. This is me getting better. Through Neuro plasticity my brain will adapt normally.

One very positive result is a now thinking and working like I did 20 years ago and incredible impact on my health has been the returning logical thinking . There are more results to eating real Whole Foods, then you realize As of two years ago, I eat only natural food

of course no sugar or alcohol or any processed food The reality is, it’s not worth it Perhaps if I would’ve known, I paid tension to the real Risk no the relative rest to Ted to see this with marketing and pharmaceuticals I would know how to continue obviously no amount of sugar, processed food or alcohol is worth stroke

There is much more to my learnings

. I would leave you with that. I’m still working as a data, governance consultant and writing books, and the improvement in my ability to think and cognition is incredible. There are many more benefits that come from Self governance– Health which I will outline in the future7 let me just say that in today’s society, there is a huge difference between “follow the science“ and real truth more important facts What Victoria has told me that today’s science, his interpretation by doctors with Me and will change overtime. However, you can see your own results make your own injections at least understand what you’re seeing versus just believe, having faith is important, but equally it is important to “trust, but verify”

That’s it right now. Thank you. Obviously, I will be going to the doctors but I will know what to expect. you get with you Inspect not what you expect and finally, obviously, the people closest to you and your life’s journey really matter

One more thing to harking back to my penis inside a video and the bases level. All of this is about extending an evolving business intelligence to artificial intelligence answer around the corner to Christian.

It starts with try again and loads and work hard we turn those word bird into actual words information to Jax Guy then within senses transformers we didn’t contact you at the senses within contact jassar‘s annual net any outcome is presented based on information and Maddie we are using better functions N maverick give availability develop in the last decade but can certainly still the same

In essence gun, that shoots is, it’s all about the information value chain

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Information Value Chain Story

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I’d would like to discuss the information, value chain and how we interpret information. However since your here and, we have time , we don’t make decisions based on data or transactions we make decisions based on information, which is in essence thru visualization and trends,, which is the result of calculations, summarizations visualization of a tremendous volume of data.

It is an is important distinguish between data and information. our perception of reality and the information we make decisions on is based on, whether or not it is accurate. Information, quality or scoring often determine how far we would go. We don’t look at the detail, we don’t want to or can’t comprehend or understand, the detail of the information we want to understand trends that will lead us to decisions to change the trends. In the next article we will examine a client I had, and which I took this journey with much detail however, the focuses on high-level impactful decision

The Takeaway is that you need to understand causality not correlation you need to understand why things happen in essence. I in brutal honesty, which is that you understand what things you can change vs thing you can’t change how you gonna affect your future reaching your goal. We will be exploring this in detail step-by-step.

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Data Governance – Navigating the Information Value Chain

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The challenge for businesses is to seek answers to questions, they do this with Metrics (KPI’s) and know the relationships of the data, organized by logical categories(dimensions) that make up the result or answer to the question. This is what constitutes the Information Value Chain

Navigation

Let’s assume that you have a business problem, a business question that needs answers and you need to know the details of the data related to the business question.

Information Value Chain

 

  • Business is based on Concepts.
  • People thinks in terms of Concepts.
  • Concepts come from Knowledge.
  • Knowledge comes from Information.
  • Information comes from Formulas.
  • Formulas determine Information relationships based on quantities.
  • Quantities come from Data.
  • Data physically exist.

In today’s fast-paced high-tech business world this basic navigation (drill thru) business concept is fundamental and seems to be overlooked, in the zeal to embrace modern technology

In our quest to embrace fresh technological capabilities, a business must realize you can only truly discover new insights when you can validate them against your business model or your businesses Information Value Chain, that is currently creating your information or results.

Today data needs to be deciphered into information in order to apply formulas to determine relationships and validate concepts, in real time.

We are inundated with technical innovations and concepts it’s important to note that business is driving these changes not necessarily technology

Business is constantly striving for a better insights, better  information and increased automation as well as the lower cost while doing these things several of these were examined

Historically though these changes were few and far between however innovation in hardware storage(technology) as well as software and compute innovations have led to a rapid unveiling of newer concepts as well as new technologies     

Demystifying the path forward.

In this article we’re going to review the basic principles of information governance required for a business measure their performance. As well as explore some of the connections to some of these new technological concepts for lowering cost       

To a large degree I think we’re going to find that why we do things has not changed significantly it’s just how, we know have different ways to do them.

It’s important while embracing new technology to keep in mind that some of the basic concepts, ideas, goals on how to properly structure and run a business have not changed even though many more insights and much more information and data is now available.

My point is in the implementing these technological advances could be worthless to the business and maybe even destructive, unless they are associated with a actual set of Business Information Goals(Measurements KPI’s) and they are linked directly with understandable Business deliverables.

And moreover prior to even considering or engaging a data science or attempt data mining you should organize your datasets capturing the relationships and apply a “scoring” or “ranking” process and be able to relate them to your business information model or Information Value Chain, with the concept of quality applied real time.  

The foundation for a business to navigate their Information Value Chain is an underlying Information Architecture. An Information Architecture typically, involves a model or concept of information that is used and applied to activities which require explicit details of complex information systems.

Subsequently a data management and databases are required, they form the foundation of your Information Value Chain, to bring this back to the Business Goal. Let’s take a quick look at the difference between relational database technology and graph technology as a part of emerging big data capabilities.

However, considering the timeframe for database technology evolution, has is introduced a cultural aspect of implementing new technology changes, basically resistance to change. Business that are running there current operations with technology and people form the 80s and 90s have a different perception of a solution then folks from the 2000s. 

Therefore, in this case regarding a technical solution “perception is not reality awarement is”. Business need to find ways to bridge the knowledge gap and increase awarement that simply embracing new technology will not fundamentally change the why a business is operates , however it will affect how.

Relational databases were introduced in 1970, and graph database technology was introduced in the mid to 2000

There are many topics included in the current Big Data concept to analyze, however the foundation is the Information Architecture, and the databases utilized to implement it.

There were some other advancements in database technology in between also however let’s focus on these two

History

1970

In a 1970s relational database, Based on mathematical Set  theory, you could pre-define the relationship of tabular (tables)   , implement them in a hardened structure, then query  them by manually joining the tables thru physically naming attributes and gain much better insight than previous database technology however if you needed a new relationship it would require manual effort and then migration of old to new , In addition your answer it was only good as the hard coding query created

2020

In  mid-2000’s the graph database was introduced , based on graph theory, that defines the relationships as tuples  containing nodes  and edges.  Graphs represent things and relationships events describes connections between things, which makes it an ideal fit for a navigating relationship. Unlike conventional table-oriented databases, graph databases (for example Neo4J, Neptune) represent entities and relationships between them. New relationships can be discovered and added easily and without migration, basically much less manual effort. 

Nodes and Edges

Graphs are made up of ‘nodes’ and ‘edges’. A node represents a ‘thing’ and an edge represents a connection between two ‘things’. The ‘thing’ in question might be a tangible object, such as an instance of an article, or a concept such as a subject area. A node can have properties (e.g. title, publication date). An edge can have a type, for example to indicate what kind of relationship the edge represents.

Takeaway.

The takeaway there are many spokes on the cultural wheel, in a business today, encompassing business acumen, technology acumen and information relationships and raw data knowledge and while they are all equally critical to success, the absolute critical step is that the logical business model defined as the Information Value Chain is maintained and enhanced.

It is a given that all business desire to lower cost and gain insight into information, it is imperative that a business maintain and improve their ability to provide accurate information that can be audited and traceable and navigate the Information Value Chain Data Science can only be achieved after a business fully understand their existing Information Architecture and strive to maintain it.

Note as I stated above an Information Architecture is not your Enterprise Architecture or even Data Architecture Information Relationships it is the hierarchical design of shared information environments; the art and science of organizing and labelling gGossary terms, transactions to support usability and findability; in an emerging community of practice focused on bringing principles of design, architecture and information science to the digital landscape. Typically, it involves a model or concept of information that is used and applied to activities which require explicit details of complex information systems.

In essence, a business needs a Rosetta stone in order translate past, current and future results.

Rosetta Stone

In future articles we’re going to explore and dive into how these new technologies can be utilized and more importantly how they relate to all the technologies.

   

 

Featured post

Data Governance Navigating the Information Value Chain Demystifying the path forward

Leave a reply

The challenge for businesses is to seek answers to questions, they do this with Metrics (KPI’s) and know the relationships of the data, organized by logical categories(dimensions) that make up the result or answer to the question. This is what constitutes the Information Value Chain

Navigation

Let’s assume that you have a business problem, a business question that needs answers and you need to know the details of the data related to the business question.

Information Value Chain

Information Value Chain

 

  • Business is based on Concepts.

 

  • People thinks in terms of Concepts.

 

  • Concepts come from Knowledge.

 

  • Knowledge comes from Information.

 

  • Information comes from Formulas.

 

  • Formulas determine Information relationships based on quantities.

 

  • Quantities come from Data.

 

  • Data physically exist.

In today’s fast-paced high-tech business world this basic navigation (drill thru) business concept is fundamental and seems to be overlooked, in the zeal to embrace modern technology

 

In our quest to embrace fresh technological capabilities, a business must realize you can only truly discover new insights when you can validate them against your business model or your businesses Information Value Chain, that is currently creating your information or results.

 

Today data needs to be deciphered into information in order to apply formulas to determine relationships and validate concepts, in real time.

 

We are inundated with technical innovations and concepts it’s important to note that business is driving these changes not necessarily technology

 

Business is constantly striving for a better insights, better  information and increased automation as well as the lower cost while doing these things several of these were examined and John Thuma’s‘  latest article

 

Historically though these changes were few and far between however innovation in hardware storage(technology) as well as software and compute innovations have led to a rapid unveiling of newer concepts as well as new technologies     

 

 

Demystifying the path forward.

In this article we’re going to review the basic principles of information governance required for a business measure their performance. As well as explore some of the connections to some of these new technological concepts for lowering cost       

To a large degree I think we’re going to find that why we do things has not changed significantly it’s just how, we know have different ways to do them.

 

It’s important while embracing new technology to keep in mind that some of the basic concepts, ideas, goals on how to properly structure and run a business have not changed even though many more insights and much more information and data is now available.

 

My point is in the implementing these technological advances could be worthless to the business and maybe even destructive, unless they are associated with a actual set of Business Information Goals(Measurements KPI’s) and they are linked directly with understandable Business deliverables.

 

And moreover prior to even considering or engaging a data science or attempt data mining you should organize your datasets capturing the relationships and apply a “scoring” or “ranking” process and be able to relate them to your business information model or Information Value Chain, with the concept of quality applied real time.  

 

The foundation for a business to navigate their Information Value Chain is an underlying Information Architecture. An Information Architecture typically, involves a model or concept of information that is used and applied to activities which require explicit details of complex information systems.

 

Subsequently a data management and databases are required, they form the foundation of your Information Value Chain, to bring this back to the Business Goal. Let’s take a quick look at the difference between relational database technology and graph technology as a part of emerging big data capabilities.

 

However, considering the timeframe for database technology evolution, has is introduced a cultural aspect of implementing new technology changes, basically resistance to change. Business that are running there current operations with technology and people form the 80s and 90s have a different perception of a solution then folks from the 2000s. 

 

Therefore, in this case regarding a technical solution “perception is not reality”, awarement is. Business need to find ways to bridge the knowledge gap and increase awarement that simply embracing new technology will not fundamentally change the why a business is operates , however it will affect how.  

 

Relational databases were introduced in 1970, and graph database technology was introduced in the mid to 2000

 

There are many topics included in the current Big Data concept to analyze, however the foundation is the Information Architecture, and the databases utilized to implement it.

 

There were some other advancements in database technology in between also however let’s focus on these two

History

 

1970

In a 1970s relational database, Based on mathematical Set theory, you could pre-define the relationship of tabular (tables) , implement them in a hardened structure, then query them by manually joining the tables thru physically naming attributes and gain much better insight than previous database technology however if you needed a new relationship it would require manual effort and then migration of old to new , In addition your answer it was only good as the hard coding query created

2020

In  mid-2000’s the graph database was introduced , based on graph theory, that defines the relationships as tuples  containing nodes  and edges.  Graphs represent things and relationships events describes connections between things, which makes it an ideal fit for a navigating relationship. Unlike conventional table-oriented databases, graph databases (for example Neo4J, Neptune) represent entities and relationships between them. New relationships can be discovered and added easily and without migration, basically much less manual effort. 

 

Nodes and Edges

Graphs are made up of ‘nodes’ and ‘edges’. A node represents a ‘thing’ and an edge represents a connection between two ‘things’. The ‘thing’ in question might be a tangible object, such as an instance of an article, or a concept such as a subject area. A node can have properties (e.g. title, publication date). An edge can have a type, for example to indicate what kind of relationship the edge represents.

Takeaway.

 

The takeaway there are many spokes on the cultural wheel, in a business today, encompassing business acumen, technology acumen and information relationships and raw data knowledge and while they are all equally critical to success, the absolute critical step is that the logical business model defined as the Information Value Chain is maintained and enhanced.

 

It is a given that all business desire to lower cost and gain insight into information, it is imperative that a business maintain and improve their ability to provide accurate information that can be audited and traceable and navigate the Information Value Chain Data Science can only be achieved after a business fully understand their existing Information Architecture and strive to maintain it.

 

Note as I stated above an Information Architecture is not your Enterprise Architecture. Information architecture is the structural design of shared information environments; the art and science of organizing and labelling websites, intranets, online communities and software to support usability and findability; and an emerging community of practice focused on bringing principles of design, architecture and information science to the digital landscape. Typically, it involves a model or concept of information that is used and applied to activities which require explicit details of complex information systems.

In essence, a business needs a Rosetta stone in order translate past, current and future results.

 

In future articles we’re going to explore and dive into how these new technologies can be utilized and more importantly how they relate to all the technologies.

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Merry Christmas Data Classification, Feature Engineering , Data Governance. ‘How to’ do it and some code take a look

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I was heavily involved in business intelligence, data warehousing and data governance as of several years ago and recently have had many chaotic personal challenges, upon returning to professional practice I have discovered things have not changed that much in 10 yearsagovernance The methodologies and approaches are still relatively consistent however the tools and techniques have changed and In my opinion not for the better, without focusing on specific tools I’ve observed that the core to data or MDM is enabling and providing a capability for classifying data into business categories or nomenclature.. and it has really not improved.

  • This basic traditional approach has not changed, in essence man AI model predicst a Metric and is wholly based on the integrity of its features or Dimensions.



Therefore I decided, to update some of the techniques and code patterns, I’ve used in the past regarding the information value chain and or record linkage , and we are going to make the results available with associated business and code examples initially with SQL Server and data bricks plus python

My good friend, Jordan Martz of DataMartz fame has greatly contrinuted to this old mans BigData enlightenment as well as Craig Campbell in updating some of the basic classification capabilities required and critical for data governance. If you would like a more detailed version of the source as well as the test data, please send me an email at iwhiteside@msn.com. Stay tuned for more update and soon we will add Neural Network capability for additional automation of “Governance Type” automated classification and confidence monitoring.

Before we focus on functionality let’s focus on methodology


Initially understand key metrics to be measured/KPI‘s their formulas and of course teh businesse’s expectation of their calculations

Immediately gather file sources and complete profiling as specified in my original article found here

Implementing the processes in my meta-data mart article would provide numerous statistics regarding integers or float field however there are some special considerations for text fields or smart codes

Before beginning classification you would employ similarity matching or fuzzy matching as described here



As I said I posted the code for this process on SQL Server Central 10 years ago here is s Python Version.

databricks-logo Roll You Own – Python Jaro_Winkler(Python)

databricks-logoroll You Own – Python Jaro_Winkler(Python)
Import Notebook
Step 1a – import pandas
import pandas

Step 2 – Import Libraries

libraries from pyspark.sql.functions import input_file_name

from pyspark.sql.types import *
import datetime, time, re, os, pandas

ML Libraires

from pyspark.ml.feature import RegexTokenizer, StopWordsRemover, NGram, HashingTF, IDF, Word2Vec, Normalizer, Imputer, VectorAssembler
from pyspark.ml import Pipeline

import mlflow

from mlflow.tracking import MLFlowClient

from sklearn.cluster import KMeans
import numpy as np
Step 3 – Test JaroWinkler

JaroWinkler(‘TRAC’,’TRACE’)
Out[5]: 0.933333
Step 4a =Implement JaroWinkler(Fuzzy Matching)

%python

def JaroWinkler(str1_in, str2_in):

if(str1_in is None or str2_in is None):
return 0

tr=0
common=0
jaro_value=0
len_str1=len(str1_in)
len_str2=len(str2_in)
column_names=[‘FID’,’FStatus’]

df_temp_table1 = pandas.DataFrame(columns=column_names)
df_temp_table2 = pandas.DataFrame(columns=column_names)

#clean_string(str1_in)
#clean_string(str2_in)

if len_str1 > len_str2:
swap_len=len_str2
len_str2=len_str1
len_str1=swap_len
swap_str=str1_in
str1_in=str2_in
str2_in=swap_str

max_len=len_str2

iCounter=1

while(iCounter <= len_str1):
df=pandas.DataFrame([[iCounter,0]], columns=column_names)
df_temp_table1=pandas.concat([df_temp_table1,df], ignore_index=True)
iCounter=iCounter+1

iCounter=1

while (iCounter <= len_str2):
df=pandas.DataFrame([[iCounter,0]], columns=column_names)
df_temp_table2=pandas.concat([df_temp_table2,df], ignore_index=True)
iCounter=iCounter+1

iCounter=1
m=round((max_len/2)-1,0)
i=1

while(i <= len_str1):
a1=str1_in[i-1]

if m >= i:
  f=1
  z=i+m 
else:
  f=i-m
  z=i+m 
if z > max_len:
  z=max_len
while (f <= z):
  a2=str2_in[int(f-1)]
  if(a2==a1 and df_temp_table2.loc[f-1].at['FStatus']==0):
    common = common + 1
    df_temp_table1.at[i-1,'FStatus']=1
    df_temp_table2.at[f-1,'FStatus']=1 
    break
  f=f+1
i=i+1

i=1
z=1
while(i <= len_str1): v1Status=df_temp_table1.loc[i-1].at[‘FStatus’] if(v1Status==1): while(z <= len_str2): v2Status=df_temp_table2.loc[z-1].at[‘FStatus’] if(v2Status==1): a1=str1_in[i-1] a2=str2_in[z-1] z=z+1 if(a1 != a2 ): tr = tr+0.5 break break i=i+1 wcd = 1.0/3.0 wrd = 1.0/3.0 wtr = 1.0/3.0 if (common != 0): jaro_value = (wcd * common)/ len_str1 + (wrd * common) / len_str2 + (wtr * (common – tr)) / common return round(jaro_value,6) Step 4b – Register JaroWinkler spark.udf.register(“JaroWinkler”, JaroWinkler) Out[6]:
Step8a – Bridge vs Master vs AssociativeALL

%sql
DROP TABLE IF EXISTS NameAssociative;
CREATE TABLE NameAssociative;

SELECT
Name
,NameInput

,sha2(replace ( NameLookput,’%[^a-Z0-9, ]%’,’ ‘) , 256) as NameLookupCeaned ,a.NameLookupKey
,sha2(replace( NameInput,’%[^a-Z0-9, ]%’,’ ‘) , 256) as NameInput,b.NameInputKey
,JaroWinkler(a.NameLookup, b.NameInput) MatchScor
,RANK() OVER (Partition by a.DetailedBUMaster ORDER BY JaroWinkler(a.NameLookupCleande, b.NameInputCleaned) DESC) NameLookup,b.NameLookupKey
FROM NameInput as a
CROSS JOIN NameLookup as b

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Trial and Tribulations of MDM (Coming Soon)

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Ira Whiteside / Jordan Martz / Victoria Stasiewicz

Advanced Matching for Business Categories(Terms) to Technical Artifacts(Data) in Relation to Master Data Management Governance and or Feature Engineering in Artificial Intelligence Modeling preparation.

We will be covering a top down(Business) and bottoms up Business driven methodology and tactical capabilities to the critical issue of associating Business categories/ dimensions to each other and subsequently transactions. We will include templates and code (Python/SQL/Databricks,etc…)….

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Eat to LIVE , do not live to EAT

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My journey to better health and the rest of my life, MINUS ==== 85 pounds, eyeball shots(needles), blood pressure meds, diabetes , they are all gone.

Pre Victoria
POSTVictoria

The ending and the beginning

It’s August 27, 2020 I’m 66 years old, and in very bad health..  My wonderful wife Tessie, passed away last night surrounded by her daughters and her grandchild.  I’m contemplating where to go from here I weigh 280 pounds, I get  Avastin shots in my eyes every six weeks,  I take blood pressure medications,  I take cholesterol medication walking is very difficult , I walk with a cane(BubbaStik).  I’ve have Diabetes Type II had two strokes, I get severe IBS(Irratible Bowel Syndrome) attacks.  I am still working , barely, Brandon and Victoria graciously take me in their home.

The beginning

In the beginning I started by just eating what Victoria ate meat, fish, salad, low carb.  Obviously I was very depressed.

Holy shit

I realize I lost 20 pounds in three months. I get laid off from work.

Really

With Brandon and Vics encouragement I start a new consulting business.

I realize I’ve lost 75 pounds in six months

PERCEPTION is not reality, AWAREMENT is reality. More on our understanding on food and the dangers of following the food pyramid recommendations

I did not go on  a diet my daughter has an approach to nutrition, Victoria’s Self Governance for health. I began to study nutrition with Vic deeper and started eating more whole foods, UNPROCESSED meat, fat, and still some vegetables what I would consider normal human food than 10,000 years ago, I didn’t count or measure anything.

Perception vs. reality

I have researched nutrition extensively and have realized that the current food pyramid guidelines are ass backwards and inverted. I will lay out the details in a later post.

Acceptance

What now. I have started  a new consulting business, Brandon and Vic , my grandaughter Julia and best friend Jordan. Vic and Brandon got me a racing Terratrike , and I am moving in an apartment. We’ll see where we go from here.

Note: Yes I still drink Red Wine – Coppolla Claret

With ICE

Featured post

Navigating the Information Value Chain

1 Reply

Data Governance

Navigating the Information Value Chain

Demystifying the path forward

The challenge for businesses is to seek answers to questions, they do this with Metrics (KPI’s) and know the relationships of the data, organized by logical categories(dimensions) that make up the result or answer to the question. This is what constitutes the Information Value Chain

Navigation

Let’s assume that you have a business problem, a business question that needs answers and you need to know the details of the data related to the business question.

Information Value Chain

Information Value Chain

 

Information Value Chain

• Business is based on Concepts.

• People thinks in terms of Concepts.

• Concepts come from Knowledge.

• Knowledge comes from Information.

• Information comes from Formulas.

• Formulas determine Information relationships based on quantities.

• Quantities come from Data.

• Data physically exist.

In today’s fast-paced high-tech business world this basic navigation (drill thru) business concept is fundamental and seems to be overlooked, in the zeal to embrace modern technology

In our quest to embrace fresh technological capabilities, a business must realize you can only truly discover new insights when you can validate them against your business model or your businesses Information Value Chain, that is currently creating your information or results.

Today data needs to be deciphered into information in order to apply formulas to determine relationships and validate concepts, in real time.

We are inundated with technical innovations and concepts it’s important to note that business is driving these changes not necessarily technology

Business is constantly striving for a better insights, better information and increased automation as well as the lower cost while doing these things several of these were examined and John Thuma’s‘ latest article

Historically though these changes were few and far between however innovation in hardware storage(technology) as well as software and compute innovations have led to a rapid unveiling of newer concepts as well as new technologies

Demystifying the path forward.

In this article we’re going to review the basic principles of information governance required for a business measure their performance. As well as explore some of the connections to some of these new technological concepts for lowering cost

To a large degree I think we’re going to find that why we do things has not changed significantly it’s just how, we now have different ways to do them.

It’s important while embracing new technology to keep in mind that some of the basic concepts, ideas, goals on how to properly structure and run a business have not changed even though many more insights and much more information and data is now available.

My point is in the implementing these technological advances could be worthless to the business and maybe even destructive, unless they are associated with a actual set of Business Information Goals(Measurements KPI’s) and they are linked directly with understandable Business deliverables.

And moreover prior to even considering or engaging a data scienkce or attempt data mining you should organize your datasets capturing the relationships and apply a “scoring” or “ranking” process and be able to relate them to your business information model or Information Value Chain, with the concept of quality applied real time.

The foundation for a business to navigate their Information Value Chain is an underlying Information Architecture. An Information Architecture typically, involves a model or concept of information that is used and applied to activities which require explicit details of complex information systems.

Subsequently a data management and databases are required, they form the foundation of your Information Value Chain, to bring this back to the Business Goal. Let’s take a quick look at the difference between relational database technology and graph technology as a part of emerging big data capabilities.

However, considering the timeframe for database technology evolution, has is introduced a cultural aspect of implementing new technology changes, basically resistance to change. Business that are running there current operations with technology and people form the 80s and 90s have a different perception of a solution then folks from the 2000s.

Therefore, in this case regarding a technical solution “perception is not reality”, awarement is. Business need to find ways to bridge the knowledge gap and increase awarement that simply embracing new technology will not fundamentally change the why a business is operates , however it will affect how.

Relational databases were introduced in 1970, and graph database technology was introduced in the mid to 2000

There are many topics included in the current Big Data concept to analyze, however the foundation is the Information Architecture, and the databases utilized to implement it.

There were some other advancements in database technology in between also however let’s focus on these two

 

History

1970

In a 1970s relational database, Based on mathematical Set theory, you could pre-define the relationship of tabular (tables) , implement them in a hardened structure, then query them by manually joining the tables thru physically naming attributes and gain much better insight than previous database technology however if you needed a new relationship it would require manual effort and then migration of old to new , In addition your answer it was only good as the hard coding query created

Early Relationship Conepts

2020

In mid-2000’s the graph database was introduced , based on graph theory, that defines the relationships as tuples containing nodes and edges. Graphs represent things and relationships events describes connections between things, which makes it an ideal fit for a navigating relationship. Unlike conventional table-oriented databases, graph databases (for example Neo4J, Neptune) represent entities and relationships between them. New relationships can be discovered and added easily and without migration, basically much less manual effort.

Nodes and Edges

Graphs are made up of ‘nodes’ and ‘edges’. A node represents a ‘thing’ and an edge represents a connection between two ‘things’. The ‘thing’ in question might be a tangible object, such as an instance of an article, or a concept such as a subject area. A node can have properties (e.g. title, publication date). An edge can have a type, for example to indicate what kind of relationship the edge represents.

Current Relationship Concepts

Takeaway.

The takeaway there are many spokes on the cultural wheel, in a business today, encompassing business acumen, technology acumen and information relationships and raw data knowledge and while they are all equally critical to success, the absolute critical step is that the logical business model defined as the Information Value Chain is maintained and enhanced.

It is a given that all business desire to lower cost and gain insight into information, it is imperative that a business maintain and improve their ability to provide accurate information that can be audited and traceable and navigate the Information Value Chain,Data Science can only be achieved after a business fully understand their existing Information Architecture and strive to maintain it.

Note as I stated above an Information Architecture is not your Enterprise Architecture. Information architecture is the structural design of shared information environments; the art and science of organizing and labelling websites, intranets, online communities and software to support usability and findability; and an emerging community of practice focused on bringing principles of design, architecture and information science to the digital landscape. Typically, it involves a model or concept of information that is used and applied to activities which require explicit details of complex information systems.

Ancient Relationship Concepts

In essence, a business needs a Rosetta stone in order translate past, current and future results.

In future articles we’re going to explore and dive into how these new technologies can be utilized and more importantly how they relate to Business outcomes

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Cancer cannot be cured, “remission” is b#llsh#t, but you can LIVE and LOVE. “Perception is not reality, awarement is reality.”

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My soulmate, my wife, my “partner“ the absolute love of my life passed away last year., NEEDLESSLY. Tessie and I put our faith in our doctors and Tessie as it should be put her faith in me, and I failed her. I didn’t cheat on Tess, I didn’t gamble, I didn’t lie, although I did drink too much, however every second of every day I feel I feel I failed.

Tessie and I survived the first occurrence of cancer in 2009. Once Tess was diagnosed she was able to take advantage of Avastin at the time a new type of immunotherapy., primarily because her idiot husband did not have insurance. Which the doctors credited with putting Tessie‘s cancer into remission, that was BULLSHIT. Eight years later I’m doctors in our regular visit told Tessie she was fine doing well and there were no signs of cancer, that was bullshit. 9 years later Tessie experienced sever back pain and was told she has sciatica, 10 years later Tessie and I were in the emergency room and it was discovered the test had multiple tumors kidney liver back ….

17 months later after much suffering and pain and at this point multiple tumors, my incredible wife passed away, and I feel as her husband.

As of today in 2021, cancer occurs in our bodies at the DNA levels. We’re told and led to believe that the issue of cancer is tumors, however it’s more basic than the issue was cancer is that are mRNA, copies are DNA to create new cells and when those cells are created they’re not coded with an expiration date. It isn’t widely known but our bodies create approximately 259 billion cells every day and in general they live only for three days, and then they die with the preschool describe date, If they don’t die, they form tumors and that is cancer.

The reason I say, that I feel I failed Tessie., is that if we would’ve not a relied on doctors and not relied on PURLEY faith and her husband would’ve done more research and realize that the only way to live longer with cancer, I emphasize the only way is to monitor and be aware of certain very low levels of substances that are accumulating in her body that can be tracked with things called cancer marker test, which generally are blood Tess’s case there is a very simple test called ACA 27/29 which basically measures the result of a certain enzyme in your blood and if that enzyme is add a measurement of 40 you’re OK, and Tessie’s case it was 4000.

In 2009 this it (CA27/29) was not revealed or taken by our doctors, and once I realized that after doing research we should’ve done years earlier Tess was told that they don’t want to do cancer marker test and they were not 100% reliable and that they wait for symptoms to occur, which in Tess’s case were massive tumors.

The point here is while they may not be 100% reliable like many things in life there can be an early indicator, even if it’s news you don’t want to hear trust me you want to know. My Tessie was fiercely independent, seriously protective of her children and her grandchildren and her husband , her family and relied on her doctors exclusively. She had “hope“ and “faith” in her doctors and God, Tess kept her faith in God however she was let down by her doctors and her husband.

The point of all this is for women and men who have been “lucky“ enough who have discovered you have cancer, you must and I repeat must get a test of your DNA and your mRNA understand mutations that exist because the various cancers she may experience and monitor them whether or not your insurance company covers his test they are critical, if you wait until a tumor

Our a wonderful daughter Victoria . who is of course supported by the worlds greatest son-in-law , has recently given a presentation to 6000 people extolling on the fact that you need to take your life your health your family and your priorities into your hands to monitor them to control them and to do everything you can to achieve the outcome you desire, obviously health and life, and love.

What frustrates me the most and why I feel I let Tessie down, is lack of knowledge which resulted from the lack of analysis. While Victoria was working on her presentation for the conference and emphasizing the need for analysis and information, in regards to meeting your health your life your goals, I realized this

Tessie is in heaven now, and I am here and thank God for Tessie‘s insistence on caring and protecting for her children and her grandchildren and her son-in-law and being protective and analytical throughout her life. However at this point I cannot stand by and not try to help informant increase awareness for other men and women that “remission“ is bullshit, there is no cure for cancer however if you monitor it and you catch it early when it’s at the cellular level and not at the tumor level you can continue to live your life experience the love of your family and your partner. there is no such thing as remission, you must get the INFORMATION you need to slow it done. You can’t prevent it, you can control it.

If anyone has any question , please let me know, I am not any kind of expert but as I tell my children “Perception is not reality, awarement is reality.”

AI LLM New Project Roles including Prompt Engineering and Role AI Scientist and integrated data and information

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I’d like to offer some advice on transitioning skills and knowledge skills and knowledge who worked hard to retainto include some of the new AI and NLM developments it’s actually less impactful, and better than you may think

Well, I dressed up in a little bit for now let’s talk about prompt engineers You most likely have currenb SME’s or expert on your current data and requirements

First, do you notice I used the term AI scientist Instead of data scientist , A data scientist Currently is actually a AI model scientist and they will help you apply. We are concerned here with how a lot of folks have opinions heuristic no not necessarily fact-based already we are going to suggest some techniques, and provide some mentoring to explore this important factor in AI is proper training we specialize in providing techniques and mentoring in separate information which is Formulated and an opinion and facts or Data, which, cannot change

There is a series of steps involved in preparing for the use of Data inAI and Chat in the form of LLM models. This is not much different and you may have most of the information already gathered in order to properly design the requirements for your model we would collect the phone.it is important to realize the steps are critical, for you have confidence in your models putput which will be your result of integrating, your Word documents, your Presentations,, spreadsheets, and, of course your actual data.

We wiKeaton, Billy, and modeling of information words versus modeling and requirements for data preparation . There is a difference that is extremely important and in line with what you’ve been doing.I know that Data preparation is not glamorous, but in my 20+ years you’ll get nowhere without proper data preparation you can’t AI it you can’t impute it you need to discuss requirements with people and write them down and then execute it The AI will make the legwork, faster. but in the end you’ll have to review it otherwiseit otherwise you may end up needlessly retracing your steps based on Improper preparation I know that Data preparation is not glamorous, but in my 20+ years you’ll get nowhere without proper data preparation you can AI it you can’t imputed you need to discuss requirements with people and write them down and then execute a I will do it. Faster time is the legwork, but in the end you’ll have to review with Stuck you may end up needlessly retracing your steps based on.I know that Data preparation is not glamorous, but in my 20+ years you’ll get nowhere without proper data preparation you can AI it you can’t imputed you need to discuss requirements with people and write them down and then execute a I will do it. Faster time is the legwork, but in the end you’ll have to review with Stuck you may end up needlessly retracing your steps based on. improper preparation. This can be at Floydd by phone, the proper steps.

1. Word document

2. Presentations

3. Spreadsheets

4.Data reports

5. Data quality report for AI preparation

6.Internet

7.Other Sources (Network,Internet or Local)

We have suggested tools/techniques/open source.and suggestions for each of these. Don’t let that bother you, however, is important with today’s capabilities in AI integrate your words your thoughts, your abstraction, and your actual data together in order for you. They’re trustworthy results from your AI.

We will be providing a separate post on each of these and then finally how they come together our point is that the what you’ve been doing to understand and form requires for tradition BI can be reutilized and extend it for AI

Data Governance and AI.

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With a little guidance, you can actually chat with the information you’ve got in caliber, or any data governance tool and integrate that with your PI Data Warehouse and the Data Marts

This would be pPossible by leveraging new capabilities, not necessarily new vendors no doubt new vendor features are on the horizon but this ability to chat with your data governance information is here now if you have already implemented the quality or MDM, or even Data Governance early adoption and prototyping of AI is possible today. We can enable this very quickly and easily by leveraging, our current, capabilities, and knowledge and tools. Who is B) in vomiting and Luigi current Lenckee or Microsoft copilot capabilities along with LLM and provide you the ability to create your own. LLM privately and insecure, basically, LM is what provides chat capability but this time with your personal data in addition, we have exceptional data quality capabilities, which can also be enhanced for you This capability will be taking traditional BI, and data governance, as well as data quality and MDM to explosive to new heights Finally, we have a decade of experience. This is merely extension of the Information Value Chain methodologies. Which we can gladly help you take advantage of

Knowledge / Training / Need to keep up with new learnings

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Currently medical guidelines and standards of care tell us and force doctors To recommend that Stan’s are good, cholesterol is bad, sugar is good, Sidor is good, saturated fat is bad. These have all been proven demonstrably fals, Our current nutrition is based on what government and medical Guidelines and standards of care that fat is bad. This is the direct cause of diabetes, obesity, and many metabolic problems.

In the 1400s if you believe the Earth was round and talked about you were killed.

What people have to realize is that what perceive as knowledge today in fact, may not be fact or knowledge tomorrow it has been that way for all time

You don’t have to be a scientist to realize that 150 years ago we did not have anywhere near astronomical rates of cancer, diabetes, obesity that we have now

What has changed is the introduction of seed, Government and the medical, and she makes like today behind Dr Ansel Keys telling us that Saturated fat that was bad. And cholesterol cause heart attacks This is false he was paid, The American heart association has revoked that claim In addition we’ve been to the sugar is OK that is salt. It lead to metabolic syndrome which leads to many Oregon, health problems, and diabetes. Tay What does it take for you to look back at 1,000,000+ years of life versus 150 years of experimental food, Created by industry for profit

As I stated in the 1400 people were killed because they did not follow the crowd and believe the Earth was flat, do you believe the Earth is flat This is only one example of many scientific facts that we hold today that Were presented over 100 years ago, and have been questioned strongly, if not disproved yet we hold why because they support certain political beliefs, or society beliefs, where is your intellectual freedom much less critical, thinking

‘Real wealth is good health’Mahatma Gandhi

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It has taken all my life, I’m 67 and of course the journey I’ve been on for the last two years to realize the truth real wealth is good health

Nevertheless, through many years of listening to commercially, driven medical and nutritional nice, I destroyed my health Yeah, what’s amazing about our bodies is with three years of Finally the good advice for my Daughter Victoria. My health has been restored.

However, I did give myself a stroke in 2014 The fact that, even though I suffered a stroke, I continued to work flying around the country supporting my famiily t denying that the condition the stroke cannot be fixed

My point is health can be restored by learning The truth unfortunately, and the conditions disability caused by stroke can’t be undone My point is health can be restored fortunately, your brain from birth has ability to learn and adapt that I have done that thankfully, it is a part of our normal body. Acceptance is crucial to recovery one of the problems I had finally is acceppting where I’m at physically . I am exceptionally blessed and that my family still supports methat mentally the damage has been mitigated and corrected.

Where I go from here is based on the full awareness of my limitations I don’t know how long I have left but then again, I never did. I do know I have no expiration date.

Another observation is having hope we talk a lot about having having however, it is within our control to have as much health as possible

Knowing the truth will require investigation on our part, and we are suffering from many misconstrued facts and Manipulated information The third leading cause of death c is medicine and side effects. It is behind cancer and heart conditions.

Ira

ChatGPT answer this?

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This White line is the time that we recorded history ,the Blue area is Pre History. So comparatively, it’s like explaining your whole life by the last 30 seconds and of course convincing everyone that you had it all figured out .

One last note by the way, we’ve only been eating the processed food we’re eating now for the last five seconds 

Full stack, developer, or jack of all trades, master of none

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Full Stack Developer

This is equivalent to asking ;someone to draft plans for your house pour the basement cement after digging the basement out , lay the bricks for the House  build the trusses for the walls and roof put the drywall in put down the trim install the cabinets and put in the lawn is the install the roof put up the the chimney , REALLY? 

Critical thinking, in data methods and modern data analytics

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Finally, in current IT and AI ,I think we are missing the forest for the trees. Actually we have been throughout the history, we have been decoding, deciphering, and learning about Logical thought, thinking we several examples, like hieroglyphics, and Socrates, obviously two ddvergent examples, one of deciphering.one, of critical thinking and I think we are missing the forest for the trees. Deep platform language that this process is a plate is in large degree Arella logical process and what was learned 2000 years of history is much much more important and relevant and relevant We seem to focus intently upon big data data analytics, etc. we seem to forget that a relationships of transactions to our derived information and thought processes for our perception which is our reality and often that is misguided. We get caught up in pursuing the truth however, we forget that the truth, for one person may not be the truth for another person hence perception. It is not a question of whether it’s right or wrong. It’s a question of what is affecting your reality, do you really care whether it’s right or wrong or you care you can change and outcome. More to come….