Ever wonder how engineers can step into a company, join a development team, and start building software right away? It’s because the way a business logically builds its database, is the exact same way their brains logically think.

Whether you’re aware of it or not, your mind is constantly building a database and storing your experiences. The steps below will give you a practical setup to those experiences. Following these simple steps will optimize memory recall, and teach you how a business creates its databases!!

The mind palace was popularized by Sherlock’s use of it in solving his cases.

The Steps

  1. Identify the user
  2. Architect the data storage
  3. Create rules
  4. Populate the data
  5. Build your intelligence

Storing Actions for Memory Recall

Example: The mind palace

It all starts with you as a user.

Step 1: User Statement

As a user, I want to remember where I’ve put everything.

Step 2: Architect the data storage

Create a detail log during your real time experiences throughout the day. With each event throughout your day representing an entry into the Actions mind table.

ActionItem TagTimestamp
WakeupSelf9/30/2018 @ 5:30 am MT
Put on ShoesShoes9/30/2018 @ 5:40 am MT
WorkoutSelf9/30/2018 @ 6:00 am MT
Eat breakfastSelf9/30/2018 @ 8:30 am MT
Go to workSelf9/30/2018 @ 9:00 am MT
Go to team stand-upSelf9/30/2018 @ 9:45 am MT
Set drink downRockstar9/30/2018 @ 9:50 am MT

NOTE: Actions can be as granular as you want them to be. 

In my personal life, my actions table is very basic and logical like the one above. It’s really only representative of the things that people see. You might choose to create a “Thoughts” table, or “Feelings” table to represent what happens that no one else can see (those tables will have a lot more entries than the actions table, or at least one would hope).

Rule Creation for New Tables

During the course of your life you’re going to start to notice trends in your Actions table. For example, I randomly leave my drink container in the many different areas I traverse throughout its short life. I seem to leave my Orange Rockstar can at everyone’s desk at work. This has led me to create a new table called Remember.

Remember table info:


Step 3: Create Rules 

Step 4: Populate the data

ShoesUpstairs bedroomTomorrow
RockstarHuddle room15 minutes

Let’s pause on the actual mind palace creation, and ask the question:

How can this help me with understanding data in business?

Good question. Let’s apply the mind palace to a very practical business application. Marketing teams, listen up!


Step 1: User Statement

I am a marketer who needs to create targeted marketing campaigns for the leads in my system.

Step 2: Architect the user actions

A business who wants this user to be successful would need to have the following tables available

Table: MarketingCampaigns

CampaignCreate Date
Awareness Q1 201811/01/2018
Nurture Q1 201811/01/2018

Table: Leads

LeadContact DateCreate Date
Analytics Odyssey10/01/2018

Step 3: Create Rules

Step 4: Populate your link of leads to campaigns

Table: campaignLeads

CampaignLeadSend DateCreate Date
Awareness Q1 2018DataTron01/01/201811/01/2018
Awareness Q1 2018Analytics Odyssey01/01/201811/01/2018
Nurture 2018RainFocus01/01/201811/01/2018

Don’t forget the last step!!

Step 5: Build your intelligence

If you’ve successfully completed steps 1-4 then you’re ready to brave the Odyssey of Intelligence. In my mind palace, imagine I’m on step 4…

ShoesUpstairs bedroomTomorrow
RockstarHuddle room15 minutes

I’m feeling tired and remember I still have half my Rockstar somewhere! The query is simple. Display the “Rockstar” rows, now grab location from the top most row. It’s as easy as that. Isn’t it?

Then why is data intelligence so hard?

This is the paradigm I’m here to tackle. I’m here to tell you that data intelligence isn’t hard. It’s simple. But you have to buy off on being data driven. Your company has to buy off on being data driven. The intelligence will come easy if the solution was architected from the beginning. However, oftentimes it is not.

The data lifecycle from identifying the user, to delivering intelligent results for strategic business decisions is a long process. It touches nearly every department in the business, and can span the course of several years. Most companies want to be more intelligent. Few take the right algorithmic approach to achieve it. True data intelligence such as Neural Networks or Logistic Regression are just a small step away. See my next blog post where we discuss data maturity and create a practical business assessment of your current analytical stage.