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Power BI and Retail Sales

Retail Sales Dashboard with Power BI The example below creates a Power BI solution to visualize retail sales data from each store.  The data is loaded into Power BI to create several views that enable everyone from store managers to regional executives to gain insights into the performance of stores and products.  Easily see the percentage of sale by different categories such as Business Segment, Region, Category or Location. To see the complete solution on PowerBI - Retail Sales Dashboard

By |2019-04-22T02:18:25+00:00July 17th, 2018|Power BI|0 Comments

Power BI and Text Mining

  Finding the Loch Ness Monster The example below uses the sighting information from LochNessSightings.com to determine the area that provides your best chance of viewing the Loch Ness Monster.  This report is based on the out of mining the text descriptions using RapidMiner to find the common nouns in the text.  Then the out is stored and visualized with Power BI to produce a heatmap with the sightings.  In your business, you can use this same technique to text mine any description fields such as call center notes, claim notes, part failure information, project notes.  To quickly spot trends or anomalies in your data. View the report here - Loch Ness Monster Sightings in Power BI  

By |2019-04-22T02:21:12+00:00July 9th, 2018|Power BI|0 Comments

Better Understand Your Credit Union Members

Increase Membership with Analytics Leverage advanced data visualization tools to better understand your members and increase membership with analytics.  By combining your credit union member information and external postal code level demographic data.  Maps can be created that color code each postal code based on the concentration of members.  For example, in the graph below postal code 78222 has 40 active members.  In addition, there are 3,685 households that earn under $50K dollars.  There are also 2,440 households that earned between $50K and $100K.  As well as 1,096 households that earn over $150K.   There is also information available for each postal code that lets you know the number of people that rent vs buy their homes, how many cars people have, average number of children and age in each household.  By using this information you can market to your existing customers like never before.  In addition, you can better understand [...]

By |2018-05-23T09:07:51+00:00May 23rd, 2018|Credit Union|0 Comments

Increase Membership and Revenue with Predictive Analytics

Credit Union Membership Increased by Data Mining I am speaking on Friday May 18th, 2018 in Savannah, GA at the National Credit Union Conference for Directors and Senior Management.  My session topic in on how to use predictive analytics to leverage your data to increase membership and revenue.   For financial institutions, the ability to determine cross selling and targeted marketing campaigns can be achieved by leveraging the data you already have.  In this session I leverage multiple technologies to put together a complete picture of member behavior, location and impact.  The image below (for my fictional credit union) shows how many members live in each postal code along with the opportunity of households in postal code.  This type of report can help you focus on areas to increase or decrease marketing to gain membership. Credit Union Member Penetration by Zipcode Session Abstract: Predictive Analytics can provide credit unions [...]

By |2018-05-18T08:46:10+00:00May 18th, 2018|Power BI, RapidMiner|0 Comments

2018 CIO Review Business Intelligence Solution Provider

CDO Advisors included in the Top 20 Business Intelligence Solution Providers We were just included as a 2018 CIO Review Business Intelligence Solution Provider. While data analytics solutions such as BI and predictive analytics have already emerged as an integral factor in bolstering the value chain of big businesses, the Small and Medium Businesses (SMB) are yet far from leveraging their impeccable benefits. The existing rumor that these services are highly expensive, and the challenge of poor data quality and sheer lack of awareness on progressive technology, have become the biggest blocks in preventing SMBs from availing data analytical services. Drawn by the situation, Derek Wilson, an astute entrepreneur endeavored on a journey to aid SMBs to extract maximum value from their data sets. Thus, saw the creation of CDO Advisors, the IT advisory and consultant firm, providing end-to-end data services ranging from data management, business intelligence, predictive analytics, to data [...]

By |2018-05-06T10:36:45+00:00May 6th, 2018|Data Mining, Power BI, RapidMiner|0 Comments

SQL Server Tabular Models (SSAS) and Power BI

Use SQL Server SSAS Tabular Models to Enhance your Power BI reports Companies with SQL Server licenses running in production most likely already own but are not using SQL Server Analysis Services (SSAS).  To get the most from your existing investment in SQL licenses.  Companies should explore how SQL Server SSAS Tabular Models  can increase the performance of their reporting environments and maximize their investment in SQL Server technology.  Transforming your data into a tabular model will allow you to get more performance from Power BI, Excel or other reporting software. Top 3 Reasons to Use SQL Server SSAS Tabular Models Speed - The data in tabular models are deployed to an in-memory data structure that makes your Power BI reports return visualizations faster than using data tables.  If your executive team hates waiting for answers or spinning circle of death Tabular models can help.  Using data compression and in-memory objects allows [...]

By |2018-04-28T16:02:53+00:00April 28th, 2018|Power BI|0 Comments

Reducing Call Center Agent Churn with Predictive Analytics

Reduce Call Center Churn Save money by reducing turnover and training cost on call center agents.  Leverage predictive analytics to reduce call center churn. Organizations that have many employees that are in high turnover positions such as call centers, sales teams, or temporary agencies. All of these roles could benefit from building models to determine why employees are leaving. Predicting employee churn using data mining and analytics can help to reduce and retain top talent. The impact of churn can be in both time and money. Time to train new hires and get them up to speed on your systems and processes. Monetary cost associated with posting for new roles, paying 3rd party agencies, paying overtime to the remaining staff and investing in employees only to have them leave within six months to a year. Read the full article here:  Reduce Agent Churn with Predictive Analytics

By |2018-04-22T10:34:39+00:00April 22nd, 2018|Data Mining|0 Comments

Primed-AP (Analytic Process)

What is the Primed-AP Methodology? CDO Advisors has launched Primed Analytics Process Homepage to publish content related to our newly published Analytic Process.  The Primed-AP © process was created based on years of experience working with business users to implement predictive analytics.  Existing methodologies focus on the data science tasks but do not include the required tasks for business users.  In order to have a successful project everyone involved needs to understand the roles and responsibilities of the entire process.  Some phases of the process require collaboration between the business and data scientist.  While other phases require more time from the data scientist.  The following section outlines the phases and highlights the responsibilities for the project team.   Full details will be available on the website that describe each step in the process along with typical tasks for business users and data scientists.  This process will enable you to get more value [...]

By |2019-04-22T13:15:10+00:00April 1st, 2018|Data Mining|0 Comments

Marketing Customer Information File Overview

  Marketing Customer Information File (MCIF) Many financial organizations already have a custom customer view called a marketing customer information file.  Other industries have these as well, called by different name such as master patient index in the healthcare space.  These files are created through existing software or internal jobs to merge data from various sources into a master file or database.  This file contains relevant information on each customer from all systems to enable a holistic view of your customers interactions with your organization.  A sample MCIF data set would include information (one row per customer) such as: Customer ID Member Tenure Checking Account Indicator Saving Account Indicator ATM Card Indicator Number of Monthly Transactions by Type Auto Loan Indicator Home Loan Indicator Last Contact Date Number of Calls to the Contact Center In addition, any other information that can be used for marketing, sales, or product development can [...]

By |2018-03-27T08:05:03+00:00March 27th, 2018|Power BI, RapidMiner|0 Comments

Speaking at the Global Predictive Analytics Conference

Implementing Predictive Analytics into Operational Workflows I will be presenting on April 3rd 2018 in Santa Clara, CA at the Global Predictive Analytics Conference.  My session focuses on how to build predictive analytics and integrate the model into your business.  I will examine two use cases: Customer Churn and Cross Selling and demonstrate the process to build the model from start to finish.  Where and how to engage with business teams to ensure the success of the project.  In addition, I will show how pilot projects build collaboration between the data science teams and business units to ensure both teams understand what is required for successful projects. For complete information on the conference - Predictive Analytics Conference Homepage

By |2018-02-27T07:14:09+00:00February 27th, 2018|Uncategorized|0 Comments