APEC Data Science & Analytics Key Competency #1: Operational Analytics

According to the APEC (Asia Pacific Economic Cooperation)  Advisory Group, Operational Analytics is one of the key competencies of a Data Science & Analytics professional working in the region.

By definition, a DSA professional uses data analytics and specialized business analytics (i.e. business intelligence) techniques for the investigation of all relevant data to derive insight in support of decision-making.

Operational analytics is made up of all the analytics processes within an organization that take data and transforms the data into actionable intelligence. In short, this is management reporting.

Without a doubt the most widely used form of analytics, management reporting is deeply ingrained into the culture of data-driven organizations.

I often liken management reporting to a pyramid. The bottom of the pyramid is the data or the base of decision-making in an organization.

The middle of the pyramid is the processes of operational analytics. Where the data is transformed.

The top of the pyramid is the decision-making. Managers need intelligence that comes in the form of insights. Great analysts deliver these insights in reports, dashboards and visualizations.

DMAIPH offers a wide range of analytics centric training solutions for professionals and students via public, in-house, on-site, and academic settings. We tailor each training event to meet the unique needs of the audience. If you need empowerment and skills enhancement to optimize the use of analytics in your organization, we are here to help.

Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to set up a free consultation to learn which of our DMAIPH analytics training solutions is best for you.

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The Rock Stars of Data: Big Data Analytics & Data Management

How to master big data analytics and data management?

The Rock Stars of Data: Big Data Analytics & Data Management

2-day Class: Big Data Analytics and Data Management

June 27-28, 2017

Discovery Suites, ADB Ave., Ortigas Center, Pasig City

9AM-5PM

Rock Stars of Data Series: Big Data Analytics & Data Management

Data Rock Stars Dan Meyer (DMAIPH) and Dominic Ligot (Cirrolytix) have joined forces to offer a unique training focusing on both the Analysis and the Management of Big Data.

To find out more about our next scheduled public learning session on May 18-19, 2017 in Ortigas or to set-up an in-house training, send an e-mail to analytics@dmaiph.com

Learning Session Description

Building The Data Value Chain. Data is pervasive – everything we do in the modern world uses and generates data in some shape or form: from web sites we surf, the social media we consume, to the mobile devices we use to connect and communicate. Modern businesses also use and generate data, from financial data, to customer data, to transaction data and sensor data.

But data is only a raw material. Regardless of amount, the real importance of data is only determined by the value people and businesses derive from it. Getting data is the first step. Then the challenge becomes transforming the raw material into a processed good: information. Information enables decisions, and decisions create value.

This session is about the basics of transforming data into information: the data value chain. Attendees will learn how to identify the right data, about how data can be efficiently stored, then transformed into a friendly form for analysis, and finally how data analysis can yield insights.

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This seminar will lightly touch on each aspect of data identification, collection, storage, transformation, and analysis and involve hands-on use of common data management and analysis tools such as Excel, Tableau and SQL, but is designed for those with little to no prior experience with these tools.

Learning Session Objectives

  1. Apply cutting edge technologies to organize, interpret, and summarize Big Data in your business.
  2. Create a process to analyze data and identify patterns not apparent at first glance
  3. Understand the components of The Data Value Chain: Ingestion, Storage, Transformation, Analysis – and how they are all important to deriving value from data.
  4. Learn database manipulation and processing basics using the Structured Query Language (SQL)
  5. Connect a data analysis tool such as MS Excel or Tableau to a database to be able to perform analysis on processed and stored data

In this session, your organization will be able to use:

  • Specific skills to effectively frame the problem you’re addressing to uncover key opportunities and drive growth
  • Critical marketing steps of orientation necessary before engaging tools and technology
  • How to simply and quickly amplify decision making by separating the signal from the noise
  • A framework for asking the right questions, allowing the ability to link analytics to business strategy

In this session, your participants will be able to:

  • Learn the best practices for organizing, summarizing, and interpreting quantitative data
  • Create a repeatable process for analyzing your data
  • Shorten the time between analysis and action to avoid “analysis paralysis”
  • Know how to get from hard data to well-reasoned conclusions

Who Should Attend

  • Business Analysts, Data Analysts and other Analytics Professionals
  • Business professionals who are involved in day-to-day analysis of data.
  • Data analysts who are already performing analysis using spreadsheets but struggle with manual data processing.
  • Managers of analysts or staff who spend a significant amount of their time collecting, analyzing and reporting data.
  • IT and Development Staff that work closely with business leaders and decision-makers.

Section One – Big Data—It’s Not Just Size That Matters

  • Understand the 3 T’s of Analytics: Talent, Technique and Technology.
  • Describe the importance of effectively, analyzing big data in Business today.
  • Develop a Data Map to analyze the Big Data in your Business.
  • Recognize when to employ Descriptive, Predictive or Prescriptive Analytics.
  • Establish clear objectives when analyzing Big Data.

Section Two – Assess Your Current Analytics Culture

  • Define What Is an Analytics Centric Culture.
  • Describe the issues and trends in today’s analytics field.
  • Discover how to find the most important KPIs.
  • Learn how to build better management reports.
  • Optimize your use of MS Excel for Big Data Analytics

Section Three – Using Business Intelligence Tools

  • An overview of BI Tools.
  • Tableau Public Demonstration,
  • Discuss the Concept of Data Visualization.
  • Build A Business Dashboard Prototype.
  • Apply a Process to Present Big Data Clearly.

Section Four – Interpreting Your Data and Analysis

  • Articulate the importance of accurately interpreting Data.
  • Determine how to validate your data analysis.
  • Mitigate and analyze Risk, Uncertainty, And Probability.
  • Spot patterns and trends through Statistical Analysis.
  • Use findings from Big Data to Drive Decisions within your Organization.

Section Five: Presenting the Data Value Chain and Databases

  • Discuss the components of The Data Value Chain and the various users and roles involved in transforming data to value: Database and ETL engineers, Data analysts, Business users.
  • Learn about basic data architecture and the role of databases in processing data.
  • Understand the basics of databases, tables and views.
  • Learn about the Structured Query Language (SQL) and SELECT statements.

Section Six: Data Processing with SQL

  • Discuss the additional value that can be derived from using SQL for Data Processing.
  • Go into detail on various ways of processing and preparing data using SQL.
  • Learn about aggregates, conditions, how to join tables, and run queries within queries.

Section Seven: Accessing SQL Tables with Excel

  • Learn about Open Database Connectivity (ODBC) and how Excel uses ODBC to connect to external data sources.
  • Discover how SQL tables and views can be read by Excel into instant Pivot Tables and Pivot Graphs.
  • Understand how changes in database table or view via SQL Inserts, Deletes, and Updates are reflected on Excel.

Section Eight: Performing analysis of SQL-based data using Excel

  • Learn about how SQL data can be dissected using the Data Analysis functions in Excel.
  • Talk about form tools and macros that can automate manual reporting.
  • Discuss tips for reporting and sharing the results of your analysis.

Minimum Hardware and Software Requirements.

  1. Laptop with Intel Core i3 and 4GB RAM.
  2. Windows OS with Excel 2007 or greater.
  3. ODBC and database connections will be provided during class.

Case Studies and Exercises

Dan and Doc will use case studies and group exercises throughout the two-day class. In these activities, the group is divided into teams. Each team will analyze datasets using the principals learned in the various learning sessions. These exercises will also use elements from the case studies as we progress from finding data, to conducting analysis on the data and finally presenting the data.

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Learning Investment for 2-day Seminar:

Exclusive Offer!!

Early Bird Rate

P 12,000.00 + VAT

(Pay the full amount on or before April 20, 2017)

Group Rate (Minimum of 5)

P13,000.00 + VAT

Regular Rate:

P 14,600.00 + Vat

(starting April 21, 2017)

All investments includes: 2-day Analytics Seminar with two of the most in-demand Analytics and Data Management Guru in the Philippines, complete with Training Materials, AM/PM Snacks, Lunch and Certificates.

ABOUT THE SPEAKERS

Dominic Ligot, Data Scientist

Doc’s areas of expertise focus on Fintech, Big Data Analytics, and Digital Transformation.

Click here to see Doc’s full speaker/trainer profile >>>

Daniel Meyer, Analytics Champion

Dan specializes in a variety of analytics themed training and speaking option including HR& Recruitment Analytics, Data Analytics, Data-Driven Decision-Making and Analytics for CEO’s.

Click here to see Dan’s full speaker/trainer profile >>>

Reserve your seat here >>>

 

Actionable Management Reporting

Except from my upcoming book on analytics for the small business owner…

One question I get asked a lot is what should someone do when they know the data they are reporting and/or using in their analysis is not the best data available?

  • Typically, Excel and PowerPoint are the primary tools used to provide management reporting to a company’s leadership. In the past few years there have been major technology innovations in business intelligence applications and data visualization software that have taken management reporting to a whole new level.
  • Recruiting has seen a huge increase in number and types of reporting tools available to deliver very fast and very detailed recruitment analytics.
  • This leads up to the concept of a business dashboard… which we will get to later.

No matter what part of the business you work in, the first thing to do is to define the current Key Performance Indicators (KPIs) being used in decision-making.  Often right off the bat, some of the KPIs being reported aren’t even being used.

You can do a simple survey, asking end users to rank in order of importance the KPIs they get. Also ask if the ones at the bottom are even useful or should they be eliminated if no one is using them.

At the same time you should be working on understanding what computations go into each KPI. Often we just do simple counts, total and averages that mask more important data. On the flip side, we tend to over complicate things with extravagant weighing and scoring. Either way, we need to make sure we know exactly what is being reported and how does the final data point come to its end state.

The next step is to look at the data architecture to make sure there is nothing happening upstream that might impact the data we are using in the KPIs. Before making changes to the KPIs we want to have the full view of what happens before the data gets to the end user.

Now we are at the point where we can start experimenting. What happens when we swap out data points? Or if we change a variable in a calculation? Or we pull the data from a different source? The questions are endless. Pick a few, make some changes in a test environment and start sharing the updated KPI data. See if it has more value with the end users.

Again, this shouldn’t be hard. But of course in many organizations a lot of consequences can result from a simple change to just one KPI. Spreadsheets may have to be reformatted, review processes may have to be updated, and dashboards may have to be redesigned. But in the end, what is more important? Making decisions with crappy data or setting a standard to let the reporting process evolve as the business evolves?

This come back to my point earlier, changing KPIs is as much sales as it is analysis… that you have to be ready to share a story, back it up with data, and really influence the minds of senior management that updating the KPIs makes good business sense.

If you are at a point where you are trying to figure out what KPIs aren’t working anymore or you need help in building a business case to change some KPIs, let me know. I’m here to help.

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Business Strategy with Analytics – Aligning a business strategy to drive an organization forward requires a robust analytics solution. Businesses who have good analytics tend to be much more profitable and efficient then ones that do not. DMAIPH has helped dozens of companies in both the U.S. and the Philippines with adding more data analysis in their business strategy. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out what we can do to help you align your business strategy with analytics.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The “DMAI” in Risk & Compliance

When it comes to risk and compliance, the most successful teams are the ones who empower data-driven decision-making through the use of analytics and business intelligence. By bringing together the best talent, cutting edge technology and tried and true methodologies risk can be optimally mitigated and compliance best achieved.

The three primary skill sets I bring to the table are data-driven decision-making, analytics and business intelligence have served me well in both my risk and compliance work with Wells Fargo and in running my own business. Finding the right data at the right time is key to seeing potential issues before they arise, quickly solving them once they do, and putting the monitoring in place to make sure they don’t happen again.

Some of the risk and compliance successes I have achieved during my career include:

  • Managed project teams on a variety of analytics and compliance initiatives while providing guidance to less experienced consultants. This includes extensive anti-money laundering research and investigation data projects for bank remittances.
  • Identified compliance training opportunities and designed compliance training materials while with Wells Fargo Commercial Mortgage on various investment products.
  • Delivered extensive training on using big data and analytics to mitigate risk and follow compliance requirements across various financial services companies in the Philippines.
  • Have worked with a variety of internal and external resources during my 15 years with Wells Fargo to provide my expertise in analytics, risk management and compliance adherence.
  • Applied my process improvement knowledge (Lean Six Sigma) and data analysis expertise to develop corrective action plans and facilitate change with several departments of Wells Fargo and with dozens on clients in the Philippines.
  • Developed comprehensive reports and business dashboards using MS Excel, Tableau and Qlikview to deliver analysis to senior business leaders to influence the establishment of risk detection and mitigation controls. Relevant reporting topics from my time in Wells Fargo Card Services include anti-money laundering, remittance limit hits, high risk customer behavior, card services usage, competitor intelligence, household cross sell, and market penetration.
  • Worked closely with IT teams at various points in my career to develop security controls, risk monitoring tools, and QA reports to determine effectiveness of payment solutions with both Wells Fargo and within my own outsourcing business. I know how to code, I know how data is structured, and I know how data should be reported when it comes to risk & compliance.

10406025_10152524531307425_1404103117_nOverall, I have 20 plus years working in positions where managing risk and meeting compliance standards are part of the daily routine.

This has gifted me with an extensive knowledge and understanding of payment products like credit cards and remittances, fraud detection and prevention, and practical experience with risk monitoring and controls.

So from my perspective, Risk Management & Compliance needs to be neck deep in data-driven Decision-Making, Analytics and business Intelligence to be able to stay ahead of the game.

Analytics Consulting – DMAIPH specializes in a variety of analytics consulting solutions designed to empower analysts, managers and leaders with the tools needed for more data-driven decision-making. We have helped dozens of companies get more analytics in their business. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can tailor an analytics solution made just for your unique requirements.

Conversation About the Reporting Mess

The other day I was hanging out with some friends who work for a company I used to work for and they were talking about challenges they were having with some reports. As I listened, images started filling my mind of the challenges so many companies face. Not having a good data strategy within a business is a killer to both productivity and morale, opens up a company to extra risk and blinds people to opportunities.

The first problem I suggested they tackle is validating their current Key Performance Indicators (KPIs). They need to analyze what is currently being reported to find out what is not useful to the business in making educated decisions.

The second problem is that the people who “own” the data don’t like sharing.  The place where I’d start with this challenges is mapping out the data flow. It would be really powerful to illustrate the different touch points within the flow and most importantly where things get stuck. Then it’s a matter of explaining the big picture to those who might be causing slowdowns.

The third problem is that everyone is too busy to sit down and figure out how to fix things. To solve this challenge, we will need to get everyone on the same page and agree to a common data strategy. This will not be a one and done meeting, but a series of conversations.

So to solve this, my friends need to start with asking questions about what do people really need. In many cases I would expect the answer is no. This is where knowing the architecture comes in handy, so you know where the data lives that is currently missing. After this it’s a matter of storytelling and influencing the “owners” of the data to understand how access to key data would generate more powerful KPIs which would allow everyone to get on the same page.

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It sounds pretty easy and it should be. The ultimate challenge is really getting people to all agree on how to use the data. In some cases, it might take senior management support to get everyone to play nice. And my friends will need data to support their argument on how thing can be better and put some numbers behind their vision of a stronger data-driven culture.

This is where I come in. When inside politics and no one has time to lead the charge, an outside consultant might be the best solution. An expert in not just identifying the challenges and sharing findings, but someone who can actually help facilitate cultural change. People who are equally skilled in both the technical world of analytics and the social world of team building are pretty rare birds.

If you are in a situation like my friends, then I’m ready to help you like I helped them.

Analytics Consulting – DMAIPH specializes in a variety of analytics consulting solutions designed to empower analysts, managers and leaders with the tools needed for more data-driven decision-making. We have helped dozens of companies get more analytics in their business. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can tailor an analytics solution made just for your unique requirements.

Mastering The Art Of Account Management

I have been thinking a lot lately about what its take manage the relationship we have with our clients.

A long time ago, I learned that to be a good account manager you need a rare combination of professional and personal characteristics, some of which can’t be taught. To me account management is the art of representing my business to clients and vice versa.

The job requires skill, advocacy, diplomacy, leadership, expectation setting, intelligence, method, heart, patience, experience, and wisdom. It is not easy and it is something I am constantly trying to improve at.

With this concept top of mind, I thought I’d share some of my tips for being an effective account manager.

  1. Under Promise and Over Deliver. I have always strived to under promise and over deliver. Most people get it wrong. They promise to something they cannot deliver and things go downhill quickly from there. Losing your client’s trust is a surefire way to doom your company.
  2. Do What They Want, Not What You Want. We often get so busy we think we have to do it the way we are doing it. Even when it’s clearly not what the client wants. This is another way to doom yourself and your business. They are paying you to do what they want, so don’t expect them to keep paying you to do what you want.
  3. Communicate Bad News Early. It is far, far better to tell you client you will be late on a deadline, or you can meet the requirement or you have to modify what you promised then it is to go silent. Not communication bad news early, or worse to communicating the bad news at all is another strike against you and your hard work, not matter what you intentions.
  4. Be the Expert. When it comes to dealing with a client, they are expecting you to know every answer, sometimes even before they ask it. They are paying you for your expertise. So you need to be the one to find problems before they are problems, fix things before they break and always have a solution at hand. If you are not an expert on what you are being paid for, they will find someone else.
  5. Always Have the Most Data. When your client tells you there is something wrong because they saw it in a report, then you know you have pretty poor analytics. You are doing the job, so you should be the one churning out the reports, championing the sharing of information and setting the agenda for the next meeting.

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That’s just a few of the things that come to mind when it comes to being a good account manager.

And just in case I need to remind anyone, and not trying to brag… but I am pretty awesome at this.

Being good at account management is without a doubt one of the key reasons I have thrived throughout my career is keeping the clients happy.

DMAIPH has successfully set up Filipino analytics teams for over a dozen U.S. based businesses. Offering both virtual and office based teams that specialize in problem solving using data, new technology and analytics techniques is our strength. Finding and empowering analytics talent is increasingly challenging, but we have it down to a science.

DMAIPH specializes in arming the Data-Driven Leader with the tools and techniques they need to build and empower an analytics centric organization. Analytics leadership requires a mastery of not just analytics skill, but also of nurturing an analytics culture. We have guided thousands of Filipino professionals to become better analytics leaders. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to discuss a uniquely tailored strategy to ensure you are the top of your game when it comes to Analytics Leadership.