(You can help forward to anyone you feel would benefit from this. Thanks.) 

The business world is now data driven and every business professional must now be fluent in the language of data. William E. Deming had the most accurate way of portraying this new age: “In God we trust; all others must bring data.” Without data skills you will have a tough time influencing in the business world. You must learn to manipulate data, make compelling data stories, leverage data for insights and drive management decisions with rich actionable dashboards.

UrBizEdge Limited, Nigeria’s leading business data analysis company is putting together these special training for proactive business professionals. It's intended for Sales Managers, Financial Analysts, Project Managers, Business Analysts, Data Analysts, NGO program managers, MIS Analysts, Strategy Analysts, Business Intelligence Analysts, HR Executives and power Excel users.

The training will be facilitated by a Microsoft recognized Excel and Power BI Expert who is also a Microsoft Certified Trainer and the only Microsoft Excel Most Valuable Professional (MVP) in Africa (there are just about 125 in the whole world and it is the highest level of recognition from Microsoft to an industry expert). He has authored bestselling books on Data Analysis using Power BI and MS Excel. We have had participants of our training from Citi Bank, Standard Chartered Bank, Dalberg, SaveTheChildren, Mobil, TCN, Chevron, Vodacom, Nestle, Christian Aid UK, Guinness Nigeria, Nigerian Breweries, Delta Afrik, LATC Marine, Broll, Habanera (JTI), Custodian and Allied Insurance, SABMiller, IBM, Airtel, Diamond Bank, Promasidor, eHealth Africa, ECOWAS, Biofem Pharmaceuticals, Ministry of Finance, FMDQ, Schlumberger, Palladium Group, Nokia Siemens Networks and DDB.

To register reach Michael on 08089382423 and mike@urbizedge.com or Hannah on 08021180874 and hannah@urbizedge.com or Emmanuel on 09084825064 and emmanuel@urbizedge.com to register. There is a class size limit.

Power BI Training Date: Friday 15th June 2018 to Saturday 16th June 2018
Venue: Kristina Jade Learning Center, 70b Olorunlogbon street, after Banex Hotel, Anthony Village, Lagos. 

Abuja Venue: Hotel Rosebud, 33 Port Harcourt crescent, off Gimbiya street, Garki 11, Abuja.

Port Harcourt Date (MS Excel): Friday 22nd June 2018 to Saturday 23rd June 2018
Port Harcourt Venue: Aldgate Hotel, 20B King Perekule street, GRA Phase 2, Port Harcourt, Rivers state. 

Lagos Venue: Kristina Jade Learning Center, 70b Olorunlogbon street, after Banex Hotel, Anthony Village, Lagos. 

The Business Intelligence with Power BI training outline is:
1.     Power BI’s strength and weakness compared to the other popular BI tools
2.     Important concepts of Power BI: real-time insights, drilldown, drill through, management dashboards, live connection, data governance, real-time collaboration, going from data to insights and from insights to action, trigger alerts, controlled access etc.
3.     Connecting to any type of data source (from structured to unstructured which will require some transforming)
4.     Getting data from existing services, organizational content pack, flat files and live databases
5.     Data Transformation (very broad and requires some knowledge of data analysis) and we will use DAX and M formulas too.
6.     Creating relationships between the datasets and leveraging hierarchy (a.k.a. data modelling)
7.     Creating Reports
8.     Visualizations and the science behind choosing the right visuals
9.     Importing custom visuals (especially word cloud for sentiment analysis and other very useful non-native visuals)
10.   Creating dashboards
11.   Publishing Reports from the Power BI Desktop and pinning to dashboards
12.   Scheduling refresh and configuring data gateways
13.   Q & A Natural Language query
14.   Integrating with Cortana
15.   Live Dashboards
16.   Collaboration and sharing
17.   Printing and Export to PowerPoint
18.   Analyzing the dashboard data (report) from Power BI service in Excel (new feature)
19.   Value Proposition to corporate customers
20.   Use case scenarios for entire company or business unit or departments
21.   Access from mobile app and setting data alerts (automated notifications when something of note happens)
22.   Lots of interaction and practice

The Excel based Data Analysis training outline is:

1) Data Manipulation in Excel 
We’ll show you, from a consultant expertise level, how to manipulate data in Excel. From data preparation/cleaning to data formatting the professional way. We’ll cover both the science and the art of data manipulation in Excel, and share very useful keyboard shortcuts and expert tricks that will speed up your productivity in Excel.

2) Data Visualization and Presentation in Excel
A picture is worth a thousand words. And in the business world, it is often the only way to not bore your audience and pass the valuable message you’ve uncovered in your data analysis. We will teach you the foundations of data visualization – from the different types of charts to when to use each of them. Then we will work through business samples to learn the art part of doing data visualization right. You will learn the rules of business data reporting via charts and gain from our industry wealth of consulting for businesses in this vital area.

3) Large Data Analysis: Pivot Table, Pivot Chart and PowerPivot
You should never say you know Excel if you don’t know how to use Pivot Table. It is that important. It is Excel’s premium tool for analysing large data – sales data, inventory data, HR data, transaction data and most business operations data. We are going to cover from the basics to the very advanced use of Pivot Tables. We will show you how to create dynamic reports with Pivot Table; how to overcome some of its layout issues; how to turn off the distracting controls in your final report; how to create calculated fields; how to create Pivot Charts; and the special tricks only a full-time Excel consultant can show you that will turbo-charge you Pivot Table skills. Then we’ll show you how we analyse data of up to (and even above) 30 million rows in Excel. Yes, in Excel. Heard of PowerPivot?

4) Business Data Analysis 
In this section, we teach you the secrets that separate the analysis experts from the people with head/academic knowledge Excel. It is one thing to know the different tools in Excel and it is another completely different thing to know how to expertly mix them together to creatively deliver value at high speed. As full-time Excel chef, we will show you the secret ingredients that make companies consult us even when they have Excel super users in their organization.

5) Executive Dashboards and Reporting
This is the level self-knowledge will not get you to. How do you create an uncrowded insightful visualization for a report with 1000s of rows? Then how about for your sales analysis report of many products and regions? How do you show the different interactions in your data? In short, how do you bring your data to life and take it from a boring confusing mass of text to an interactive exciting visualization? You have to come to get the answers.

6) Excel to PowerPoint
Management level reports are best presented in PowerPoints. When you’ve got a delicate story to tell, you have to guide your audience through a one idea/insight a slide PowerPoint. We won’t teach you how to design slides but we will teach you how to make your chart slides speak very loud. You will also learn the tricks of linking your PowerPoint charts to Excel. It will help cut down the hours you spend on weekly/monthly PowerPoint reports. We will also show you how to embed Excel files in your PowerPoint slide. No more sending separate Excel files when you can embed them right on the very slide you reference their data.

7) Excel VBA
Forget about all you’ve heard about Macros or VBA. Let’s show you how easy and exciting it is to break into the Excel VBA world.

To register reach Michael on 08089382423 and mike@urbizedge.com or Hannah on 08021180874 and hannah@urbizedge.com or Emmanuel on 09084825064 and emmanuel@urbizedge.com to register. There is a class size limit.

For a taste of our high quality content, view our free tutorial videos at www.urbizedge.com/tutorials

Today's guest post is on the fundamentals of building wealth. The only edit I felt tempted to include is paraphrase the source of true wealth to point to God using our mind. Enjoy!
image: greatperformersacademy.com

Believe it or not, you are not supposed to be poor. Living in lack, begging, borrowing from paycheck to paycheck and swimming in debt was not God’s plan for man. Man was supposed to dominate his environment. Sadly today more than three quarters of the earth’s population live in extreme poverty.
Poverty was my reality until I discovered the source of true wealth and riches. By true wealth and riches I am not referring to gold, or other mineral deposits that can be found on the earth. The source of true wealth and riches is the mind, from where every great wealth emanates from. Wealth has to be thought of first before it becomes reality. In other words it is thought that produces wealth.

Now for the mind to be able to effectively kick start wealth creation it must be free of self-limiting beliefs. These beliefs are falsehoods that we see as true. This causes many people to fail to achieve their financial potential because it is what you believe that becomes reality. Here are twelve of such self-limiting beliefs that held me back from financial success in the past:

Riches are the result of spiritual activity
Self-limiting belief number one for me was that riches are the result of spiritual activity. In order to become wealthy all I needed to do was to fast and pray, attend church programs and vigils. And voila my efforts would lead to financial breakthrough. No way. This does not work! In fact most of the richest people in the world are the least religious with very few believing that God exists. Spiritual activity can only point one in the right direction as to what needs doing, it can’t produce wealth by itself.

Lack of connections
Lack of connections was the second belief that I felt was a hindrance to becoming wealthy. I needed to know the right people who would help me achieve my goals. Not having any connections meant I could never become wealthy. How wrong I was! Nobody is born with connections; rather they are the result of years of deliberate cultivation.  As I continued to work hard and build relationships I gradually started building my network of contacts. These eventually became my connections and have assisted me on the way up the financial ladder. You too can do the same.

I need to relocate to make it financially
Thirdly, it is not possible to make it in my country Nigeria. I needed to relocate abroad in order to make it. That is a lie. Go to the International Airport and see the amount of foreigners trooping into Nigeria on a daily basis. They are not here for sightseeing. Even the international business community sees Nigeria as a huge investment opportunity that many want to cash in on. Can this be the same Nigeria that I wanted to run out of that many people are running to? This land is truly green with opportunity. I am now making it in Nigeria.

Rich people are lucky
Fourth, the rich are lucky. They have luck on their side, and poor me didn’t qualify to be part of the lucky stakes. Now I know better. There is no such thing as luck. Rather there are favourable situations that can benefit you when opportunity comes and you are prepared for it. I kept preparing and preparing and one day things fell in place like clockwork. My opportunity came and because I was prepared I was able to grab it with both hands.

Lack of Capital
The fifth limiting belief was lack of capital. Without money I could not take advantage of opportunities that came my way. I find that this is one of the self-limiting beliefs hindering many people from building wealth. In order to defeat this I pursued my dreams on a small scale for starters, and sought for funds from friends and loved ones. I even put some of my dreams on hold while saving startup money. Lack of money is not an excuse not to start something.

Lost opportunities can't be regained
Self-limiting belief number six is the famous saying, “opportunity knocks but once". I used to believe this statement, which alluded to the fact that missed opportunities never return. With all due respect to the author of this statement I have discovered that lost opportunities do return.  But in another form. Opportunity keeps knocking and sooner or later as long as I was prepared I would be able to take advantage.

Failing to harness the power of my imagination
Failing to harness the power of my imagination was the seventh self-limiting belief causing me not to progress financially. There is a lot of power in one’s imagination. The imagination is the eye of the mind that helps you first internalize what you want to see in your life. In other words I needed to imagine myself as wealthy and successful in my mind before I could attain it. Unfortunately my mind chose to internalize my poor state instead. It was when I started focusing on the right images that things began to improve.

Underestimating my abilities regarding wealth creation
Eighth, I was very guilty of underestimating my abilities regarding success and wealth creation. When you believe that you are an undeserving and unworthy candidate for wealth, then wealth wants to be far away from you. I came to myself and replaced those thoughts with positive ones proclaiming the fact that I deserved to be rich. It was my place to control financial resources and I was as good as anyone trying hard to build wealth.

The current economic situation
Ninth, the current economic situation could be such a major hindrance. I was wont to believe that wealth and riches cannot be amassed during times of economic crisis and recession. Nothing could be further from the truth. It is in times of adversity and challenges that some rise to the occasion thereby creating wealth for themselves. Economic crisis may be fraught with challenges but it's also a time of opportunity. I don't let the current economic situation cause me to believe that it is impossible to be wealthy.

No one in my family had amassed substantial wealth
By far one of the strongest self-limiting beliefs I had to contend with was that no one in my family had amassed massive wealth and fortune. What are the chances of succeeding when no one else in my lineage was up to the task? I was only able to defeat this notion of not succeeding by reading books of many successful people. In my studies I was pleasantly surprised to learn that many of today’s financial successes are also the first people in their families to amass stupendous fortune. If they could do it then I could too.

You cannot be rich without being fraudulent
Self-limiting belief number eleven strives to make it clear that one cannot succeed without engaging in criminal acts. It seeks to demonise everyone who is wealthy as being involved in one shady activity or the other. In fact it maintains that wealth abstains from those who are honest and upright in their dealings. Again it was while studying the lives of rich people that I found that there are many honest and upright rich people in our society. It's just that they are not often celebrated. Their stories made me believe it is possible to make wealth the right way.

Having lots of money is evil
My twelfth self-limiting belief concerns my desire and dream to amass wealth. I used to think that amassing lots of money was evil. Wealth would cause me to lose focus and compromise my faith and principles. Society paints the picture of the rich as greedy and desperate people who keep wanting more and more. The truth is there’s nothing wrong in desiring plenty of money. What's wrong is when you compromise to get it and you love it more than anything else in your life.  As long as my motives were grounded and I did not let money become my God I was free to gather as much as I could.

My final word on self-limiting beliefs
The mind is a battleground. If you desire wealth then you must infuse the mind with wealthy thoughts and beliefs. Failure to do so will cause you to stagnate financially.  There's usually something holding us back from going after our goals and achieving our potential right in our minds. Once we can identify and neutralize these self-limiting beliefs we are well on our way to achieving wealth.
Now this list is by no means exhaustive. I urge you to take time out now and examine everything you believe about money. Write them down and engage in a painstaking review. Make the necessary changes should you discover any of these self-limiting beliefs hold true for you. I make bold to declare that one of the major reasons you are not rich today is because you have self-limiting beliefs about money operating in your life at the moment.

Author's Profile
Kenneth Doghudje is intensely committed to seeing people achieve their financial goals and aspirations in Africa. A CEO by day and a Blogger by night, he believes that the secret to anyone succeeding financially is to mix workable insights with action which translates to wealth and riches.
Please endeavor to visit www.moneytalkNG.com for more articles on money and personal finance. You can also sign up for moneytalkNG’s newsletter where Kenneth dispenses financial wisdom by clicking here to receive latest insights direct into your mailbox.

Yesterday, I demoed how in 10 mins you can create a predictive model, deploy it as a web service and test it without having to install anything or pay any money. That is the awesomeness made possible by Microsoft with the super easy to use Azure Machine Learning Studio. The yesterday event was the Lagos edition of the Global Azure Bootcamp held at Microsoft office, Lagos.

Participants were able to follow along, created and deployed their own predictive models too. In today's post I will be guiding you with easy steps to follow on how you too can in a few minutes create and deploy a predictive model cost-free with Azure Machine Learning Studio.

Step 1
Download the sample data we would use: Bank Marketing data from UCI Machine Learning Repository. If you download from UCI Machine Learning Repository directly, then it is the bank-additional-full.csv file in the zip file you end up with. Then you have to make sure that you break the data into separate columns rather than leave them comma separated, using Excel's Text to Columns. For you ease, I have shared a cleaned version you can directly use without any extra work by you: Bank Marketing data download

The sample data is a marketing campaign data of a Portuguese bank from May 2008 to November 2010 recording the details of prospects reached via phone calls and whether they eventually took up the service the bank was trying to sell them.
The cleaned sample data
Below is the explanation of the different fields in the data records.

Input variables:
# bank client data:
1 - age (numeric)
2 - job : type of job (categorical: 'admin.','blue-collar','entrepreneur','housemaid','management','retired','self-employed','services','student','technician','unemployed','unknown')
3 - marital : marital status (categorical: 'divorced','married','single','unknown'; note: 'divorced' means divorced or widowed)
4 - education (categorical: 'basic.4y','basic.6y','basic.9y','high.school','illiterate','professional.course','university.degree','unknown')
5 - default: has credit in default? (categorical: 'no','yes','unknown')
6 - housing: has housing loan? (categorical: 'no','yes','unknown')
7 - loan: has personal loan? (categorical: 'no','yes','unknown')
# related with the last contact of the current campaign:
8 - contact: contact communication type (categorical: 'cellular','telephone') 
9 - month: last contact month of year (categorical: 'jan', 'feb', 'mar', ..., 'nov', 'dec')
10 - day_of_week: last contact day of the week (categorical: 'mon','tue','wed','thu','fri')
11 - duration: last contact duration, in seconds (numeric). Important note: this attribute highly affects the output target (e.g., if duration=0 then y='no'). Yet, the duration is not known before a call is performed. Also, after the end of the call y is obviously known. Thus, this input should only be included for benchmark purposes and should be discarded if the intention is to have a realistic predictive model.
# other attributes:
12 - campaign: number of contacts performed during this campaign and for this client (numeric, includes last contact)
13 - pdays: number of days that passed by after the client was last contacted from a previous campaign (numeric; 999 means client was not previously contacted)
14 - previous: number of contacts performed before this campaign and for this client (numeric)
15 - poutcome: outcome of the previous marketing campaign (categorical: 'failure','nonexistent','success')
# social and economic context attributes
16 - emp.var.rate: employment variation rate - quarterly indicator (numeric)
17 - cons.price.idx: consumer price index - monthly indicator (numeric) 
18 - cons.conf.idx: consumer confidence index - monthly indicator (numeric) 
19 - euribor3m: euribor 3 month rate - daily indicator (numeric)
20 - nr.employed: number of employees - quarterly indicator (numeric)

Output variable (desired target):
21 - y - has the client subscribed a term deposit? (binary: 'yes','no')

Step 2
Sign up for Azure ML studio. It is easy and free: https://studio.azureml.net 

Step 3
Upload the Bank Marketing dataset. From Datasets section on the left menu pane, click New at the bottom left.

Step 4
Create a new experiment. From Experiments section on the left menu pane, click New at the bottom left. Choose a blank experiment, as we are creating ours from scratch.

Step 5
Now we start dragging the tasks we want to carry out into the Experiment workspace, after renaming the Experiment.

Drag in the dataset we uploaded, it is in the Saved Dataset section on the left.

Next, we need to isolate the fields that would be useful for our predictive model. If you look at the description of all the fields in the dataset, it is obvious that some are not practically useful in creating a prediction of whether a prospect will take up the marketed service or not. Example is the length of the call, there is no way you would know that until the end of the call -- so not useful for profiling who to call (targeted marketing). By my thinking, the fields I that would be of real world use in creating an actionable predictive model are -- age, job, marital, education, default, housing, loan.

Drag Select Columns in Dataset in the Manipulation subsection of Data Transformation section. Connect the dataset previously dragged in to the select columns task. Then click on Launch column selector, and select the columns needed (including the outcome we want to predict, so as to be able to train the model).

Next, split the data into training set and testing set for building our predictive model. Drag Split Data, connect to the select columns task and on the settings pane on the right, set the training set to 0.75 (75%) of the entire dataset.

Drag in the model algorithm to use. It's under the Initialize Model. I chose to use the Two-Class Decision Forest. In the end, you would evaluate the model to see if it fits well or you should try another algorithm.

Drag in Train Model. Connect to both the already dragged in algorithm and the left side of the Split Data (training set). Select the outcome to predict.

Drag in Score Model. Connect to the Train Model and the testing set of the Split Data.

Lastly, drag in Evaluate Model. Connect to Score Model.

Now run the entire experiment.

Wait for it to finish running.

Right click on Evaluate Model and visualize the evaluation result to see the fitness/accuracy of the algorithm.

If you are okay with the fit, then what's left is to publish. Otherwise, you can change the algorithm, re-run and re-evaluate the fit.

Step 6
Now you set up the model as a web service that can be deployed online.

Change the input connector to point to the Score Model. 

Also, remove the predicted column from the Selected Column as it was only needed for training the model.

Now re-run and deploy as web service.

You are presented with the web service details to use for integrating with any app or online tool. You can even test the API directly.

And that's how you create and deploy a predictive model in Azure Machine Learning Studio without installing anything on your computer and without paying a cent/kobo.

Creating my Nigerian Market Data app (stocks, economic and fx rates app) involved setting up an Azure VM that I run a couple of Python scripts on daily. 

I used Windows Task Scheduler to automate the Python scripts to run between 9:20 pm and 11:00 pm. It wouldn't make sense to keep the server (Azure VM) running all day. So I set up an automation on Azure to start up the server at 9:00 pm and shut it down by midnight. Below are the steps to doing this.

If you run a search online, you will come across multiple ways to doing this. Some require you writing Powershell scripts. The method I am going to illustrate is the least error prone and most straightforward way I have come across.

Step 1: Log into your Azure account portal

Click on Create a resource.

Step 2: Search for Automation

Click on Automation.

Step 3: Create a new Automation

Step 4: Complete the Automation Account Creation
Make sure to tick use existing resource group, and pick the resource group of the VM you want to auto shutdown/startup. Also best to match the location selection.

Step 5: Add Startup and Shutdown Runbooks to the Automation Account
Select the automation account you just created.

Select Runbook under Process Automation. And click on Browse gallery. This allows you to create the startup and shutdown automation runbooks.

Click on Edit in the created Runbook

Then publish the runbook.

Click on Schedule after publishing.

Set the Time to run the Start VM runbook by clicking on "Link a Schedule to your runbook"

Lastly, set the parameters which will link it to the VM you want to control. Make sure you match the resource group and VM name. You can leave the AzureConnectionAssetName blank so the default is used.

Now you repeat same steps for Shutdown runbook after picking from the runbook gallery.

Step 6: Sit back and watch the automation runbooks do their work

You can monitor the runbook activities from Jobs in the Runbook Overview.

And that's all!