Analytics Centric Cultures – Learn More June 5-7, 2018 in Ortigas

Inspired in part by Bernard Marr’s 2010 book, The Intelligent Company, my goal these past several years has been to build and/or be part of data-driven business cultures. The description of the book on Amazon sums it up well, “Today’s most successful companies are Intelligent Companies that use the best available data to inform their decision-making.”

In his book, Bernard advocates for using Evidence-Based Management that is using the best available data to inform decision-makers. In parallel to this, I have been empowering companies and professionals to empower decision-makers to use more data as well. I call it data-driven decision-making, but at their cores, there are very similar approaches to managing success.

The cornerstone of the book is the five steps to more intelligent decision-making, which are:

  • Step 1. More intelligent strategies — by identifying strategic priorities and agreeing your real information needs
  • Step 2. More intelligent data — by creating relevant and meaningful performance indicators and qualitative management information linked back to your strategic information needs
  • Step 3. More intelligent insights — by using good evidence to test and prove ideas and by analyzing the data to gain robust and reliable insights
  • Step 4. More intelligent communication — by creating informative and engaging management information packs and dashboards that provide the essential information, packaged in an easy-to-read way
  • Step 5. More intelligent decision-making — by fostering an evidence-based culture of turning information into actionable knowledge and real decisions.

As information and data volumes grow at explosive rates, the challenges of managing this information is turning into a losing battle for most companies. In the end they find themselves drowning in data while thirsting for insights. Combine this with an increasingly severe shortage of talent with analytics, data visualization and good communication skills, things look bleak for companies not adhering to lessons like those suggested in the Intelligent Company.

In addition, Data-Driven Cultures Do These Things:

  1. They embrace Big Data. They aren’t afraid of it. They relish the addition of new data sources and actively look for more.
  2. Managers use Evidence-Based Management techniques. Just about every choice comes based on data analysis.
  3. Challenges are addressed with Data. When something happens that was unexpected, the challenge is met with a data centric approach.
  4. The right data is being used. A lot of work goes into validating data and keeping it clean and fresh. The concept of having a data lake that supports multiple parts of the business is in place.
  5. They have the right analytics talent. Analysts are empowered to go out and discover not just current challenges, but look for potential ones as well.
  6. They know how to communicate. The sharing of information is done to benefit everyone. You won’t see lots of data trapped in silos. Data has no one true owner.
  7. They take action based on their data and analysis. You don’t see a lot of useless reports that kills a small forest or clog up an inbox with massive files. They keep it smart and simple.

Data-Driven cultures are a lot harder to find than they should be. In this day and age, every company should have a strategy on how to use data to drive more intelligent decisions, but they don’t. Success eludes many companies because they don’t have the 7 qualities listed above in place. If you were to ask what they look like it would be something akin to this:

· Top management is afraid of data. Senior leaders don’t even know how to use MS Excel. There is no analytics champion in the organization to spearhead data projects.

· Decisions are made based on what worked in the past, relying on experience and gut feel. There is little evidence used to go in any certain direction.

· When things don’t work out, data and analysts take the blame. You will hear a lot of “why didn’t you tell me” and “I didn’t see it coming” excuses.

· What data is being used is old, dirty, incomplete, full of errors and doesn’t tell the whole story. Reports are basically useless and just produced to look at what people generally already know. They look for what’s there, oblivious to what’s not.

· They do not share data. They hoard it. They don’t trust anyone else with access to it. The data is stored in unconnected storage places. There is no common understanding how to use data.

· They fail a lot. Success generally happens by hard work as much as luck. It’s impossible to know for sure what caused what to happen.

It’s not easy to take a company that has little or no data-driven decision-making and turn it into an Intelligent Company, but it can be done. I have done it. I have guided transitions from the stone-age to the information age. Let me show you how.

I will cover all these concepts in more in upcoming my training class on June 5-7, 2018 at Discovery Suites in Ortigas. For a list of training events, please visit www.sonicanalytics.com

Dan Meyer heads Sonic Analytics, an analytics training, consulting and outsourcing company with offices in Manila and the San Francisco Bay Area. With over 20 years in Big Data, Dan is one of the most sought after public speakers in Asia and has recently begun offering public training seminars in the United States.

We need to look at the data (analytics), plan a course of action (strategy) and share our data-driven viewpoints (presentation). So he has started an internship program under Sonic Analytics to empower the youth the use Analytic, plan Strategy and Present their views… ASP!

Sonic Analytics(www.sonicanalytics.com) brings big data analytics solutions like business intelligence, business dashboards and data storytelling to small and medium sized business looking to enhance their data-driven decision-making capabilities.

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Finding the Right Data

“Data! Data! Data! I can’t make bricks without clay!”

-Sir Arthur Conan Doyle

Sir Conan Doyle’s famous fictional detective, Sherlock Holmes, couldn’t form any theories or draw any conclusions until he had sufficient data. Data is the basic building block of everything we do in analytics: the reports we build, the analysis we perform, the decisions we influence, and the optimizations we derive.

Finding the Right Data at the Right Time

Back at Wells Fargo, the single greatest attribute that made me successful was my ability to size up how long it would take to deliver something. Knowing what data I would need, where I would find it and how long it would take to analyze it to come up with something useful made me somewhat of a wizard in the minds of the team.

Finding the right data at the right time requires one to first know ends and outs of their data. You have to know how the data is captured, where it is stored and how it makes its way to you. Knowing the data architecture in your business is the key.

So you have to get to know the people who know where your data comes from and how it gets there. Learn from them. Partner with them. Buy them doughnuts.

A few years ago I came across an analogy being used to describe data in a business. That of a data lake. A data lake is the living, breathing, evolving pool of all the data in a business. If you have a good data architecture, and you can navigate it fairly easily, then you have a data lake. Ideally, your business has data structured in such a way you can live off it. Data to a business is like water to living things… it sustains life

So once you have the lake mapped out, then you have to learn how to fish it. Knowing where the fish are biting is another key. Once you know what data you need, you have to know how to get to it quickly.

I can’t stress this enough. No matter how good you are at analysis, or what tool you are using to do the analysis, if you don’t have an understanding of what happens to the data before it gets to you then you are probably not drinking from a clean lake.

Business Intelligence tools help us here. As does coding languages to extract data from a database. These are your fishing tools. You have to practice using them to be good at getting the right data at the right time.

Another way to optimize your data search is to save your work. Of as I call it leave yourself breadcrumbs. Save the query. Cut and paste the code into a document and save it. Write down the steps. Whatever you need to do to replicate what you just did so you can do it again in the future without starting over from scratch.

So to recap, if you know data structure, you understand how data is stored and you leave yourself clues to do things faster next time.

Now the other part of the equation is knowing if the data you are using is the right data. Finding data quickly doesn’t do you any good if you bring back the wrong data.

So, how do you know if the data you are using is the right data to be using?

I can’t count the number of times I asked myself that question. In general, just about every new analysis or project or research or whatever it is you are using data for, you have to ask that question at some point.

Even data you have used a hundred times and comes from a highly trusted source needs to be scrutinized.

Now if you work with data every day in a familiar format, from the same source and with no changes to the data gathering and storage process you don’t have to spend much time validating it. Usually you will see problems when something just doesn’t look right when you are doing the analysis.

On the other hand, things get a whole lot trickier when you are using data from a source you don’t use often, or something has changed in the way the data is populated or if it’s the first time you are using the data.

When this happens, I have a few suggestions on how to validate the data.

· First off, pull the data, do your analysis and draw some conclusions. If it passed the eye test and it feels ok to you, then your job is just to validate it.

· One simple way to do this is pull the data again the exact same way to make sure you get the exact same data. Or change one parameter like the dates used in the query. See if that significantly alters the way the data looks and feels.

· Another option is to have someone else do the same thing independently. See if they get the same results you do. You can also find someone who knows the data to look over your work to see if it makes sense to them.

In the end, whatever you do, make sure you have the right data.

I will cover all these concepts in more in upcoming my training classes. For a list of training events, please visit www.sonicanalytics.com

I’ll be conducting the following business analytics trainings over the next few months:

· June 5 in Ortigas (Metro Manila, Philippines)

· July 17, in Pleasant Hlll, CA (San Francisco Bay Area, US)

· August 22, in Bonifacio Global City (Metro Manila, Philippines)

Dan Meyer heads Sonic Analytics, an analytics training, consulting and outsourcing company with offices in Manila and the San Francisco Bay Area. With over 20 years in Big Data, Dan is one of the most sought after public speakers in Asia and has recently begun offering public training seminars in the United States.

We need to look at the data (analytics), plan a course of action (strategy) and share our data-driven viewpoints (presentation). So he has started an internship program under Sonic Analytics to empower the youth the use Analytic, plan Strategy and Present their views… ASP!

Sonic Analytics(www.sonicanalytics.com) brings big data analytics solutions like business intelligence, business dashboards and data storytelling to small and medium sized business looking to enhance their data-driven decision-making capabilities.

What is Business Analytics? In Most Cases It’s Simply Excel & 3 Bullet Points

Business Analytics refers to the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight, discover opportunities and/or drive business planning. *https://en.wikipedia.org/wiki/Analytics

The most common form of analytics is business analytics that are generally used by senior leaders and decision-makers to investigate problems, validate assumptions and to guide strategic planning.

Business analysts are therefore the most common type of analyst. If you do a job search on the title analyst, as many as half the posting will likely be business analysts. However, analytics can be used in an almost limitless number of business functions in specific areas like HR, recruitment, marketing, finance, and so on. Each one can have its very own analyst.

I was a business analyst for a large part of my career at Wells Fargo, but even before I had analyst in my title I was heavily involved in business analysis. Why?

Because I know how to use Excel.

It’s amazing how many people are scared of Excel. To many highly educated and successful business leaders across Corporate America, making a pivot table in Excel is like magic.

If you were able to take an honest survey of managers and supervisors across the country (world actually), you would probably be quite surprised by the high percentage who would prefer to find someone else to analyze their data.

That’s one of the biggest reasons business analysts are so prevalent.

Another is time.

I had a boss at one point that grilled into me the philosophy that no matter how much data you have, and how complex the analysis, it’s all worthless if you can’t boil it down to 2–3 bullet points.

That’s all he had time for.

3 Bullet Points!

So being a successful business analyst really require 2 skills; Excel and condensing data into 3 bullet points.

If you can do that, you’ll go far.

I did.

A business needs analysts to make sense of big data, manage the storage of the data, and know when to use which of the 4 types of analytics (descriptive, diagnostic, predictive, and prescriptive). To be effective, analysts need to have business intelligence tools to create data visualizations and build business dashboards.

I will cover all these concepts in more in upcoming my training classes. For a list of training events, please visit www.sonicanalytics.com

I’ll be conducting the following business analytics trainings over the next few months:

· June 5 in Ortigas (Metro Manila, Philippines)

· July 17, in Pleasant Hlll, CA (San Francisco Bay Area, US)

· August 22, in Bonifacio Global City (Metro Manila, Philippines)

· September 4, Rancho Cucamonga (North of Los Angeles, US)

Dan Meyer heads Sonic Analytics, an analytics training, consulting and outsourcing company with offices in Manila and the San Francisco Bay Area. With over 20 years in Big Data, Dan is one of the most sought after public speakers in Asia and has recently begun offering public training seminars in the United States.

We need to look at the data (analytics), plan a course of action (strategy) and share our data-driven viewpoints (presentation). So he has started an internship program under Sonic Analytics to empower the youth the use Analytic, plan Strategy and Present their views… ASP!

Sonic Analytics(www.sonicanalytics.com) brings big data analytics solutions like business intelligence, business dashboards and data storytelling to small and medium sized business looking to enhance their data-driven decision-making capabilities.

Getting Started With Analytics

The primary people responsible for conducting analytics on the massive amounts of data we have today are analysts.

Analysts are skilled in using various technologies and methodologies to identify, inventory and integrate large amounts of data quickly.

A general definition of an analyst is a person who analyzes or who is skilled in analysis. Analysts examine things carefully and in detail so as to identify causes, key factors, possible results, etc. generally using a process of identifying, inventorying and integrating data. *http://www.dictionary.com/analyst

I often hear that most analysts today feel like they are drowning in a sea of data. They need to know how to take control of their data and analysis to quickly answer business questions and make critical decisions. They want to confidently present results and solutions to their managers, colleagues and clients.

You most likely clicked to this page because you fit the description above. If that is the case, then you made a good decision. 😉

All kidding aside, I have designed a method to help you look at analytics in a way that will make data and analysis easier to understand and conduct. My trainings and published content will also instruct you on how to share data in a more dynamic and influential way.

Analysts have been around a long time, but recent technological advances have both allowed us to produce and capture more data as well as give us the ability to analyze immense data sets quickly. Thus we are amidst a huge boom in the applications of analytics and the need for analytics talent across the globe. Analytics is something just about every business leader is trying to figure out how to use more effectively in their business. To add to our challenge, the demand for good analysts is booming just as fast as the explosion in big data.

As a result, there is a huge shortage of people who are skilled in working with data to answer questions and solve problems. This is why you have seen the number of analyst job postings increasing at an amazing rate. In fact the quickening demand for analytics talent has made it very hard for most businesses to find good analysts.

If you are a business leader, manager, owner, and/or executive are not actively trying to surround yourself with analysts and if you are not infusing an analytics centric culture in your business, you will most likely soon see your business fail.

Keep in mind that analytics is about looking for patterns in data to help answer questions. Most businesses use analytics to help ensure more data-driven decision-making.

The primary people responsible for conducting analytics on the massive amounts of data we have today are analysts. Do you have analysts on your team?

Analysts are skilled in using various technologies and methodologies to identify, inventory and integrate large amounts of data quickly. Are you an analyst yourself?

If you answered yes to either question, but you feel you need more training for yourself or your team, you are not alone.

A business needs analysts to make sense of big data, manage the storage of the data, and know when to use which of the 4 types of analytics (descriptive, diagnostic, predictive, and prescriptive). To be effective, analysts need to have business intelligence tools to create data visualizations and build business dashboards.

I will cover all these concepts in more in upcoming my training classes. The classes are designed specifcally for people new to analytics and for business leaders looking to upgrade the level of analytics in their business.

For a list of training events, please visit www.sonicanalytics.com

Upcoming Training Dates

· June 5 in Ortigas (Metro Manila, Philippines)

· July 17, in Pleasant Hlll, CA (San Francisco Bay Area, US)

· August 14, Rancho Cucamonga (North of Los Angeles, US)

· August 22, in Bonifacio Global City (Metro Manila, Philippines)

My goal with this series is to help you look at analytics in a way that will make data and analysis easier to understand and conduct.

Dan Meyer heads Sonic Analytics, an analytics training, consulting and outsourcing company with offices in Manila and the San Francisco Bay Area. With over 20 years in Big Data, Dan is one of the most sought after public speakers in Asia and has recently begun offering public training seminars in the United States.

We need to look at the data (analytics), plan a course of action (strategy) and share our data-driven viewpoints (presentation). So he has started an internship program under Sonic Analytics to empower the youth the use Analytic, plan Strategy and Present their views… ASP!

Sonic Analytics(www.sonicanalytics.com) brings big data analytics solutions like business intelligence, business dashboards and data storytelling to small and medium sized business looking to enhance their data-driven decision-making capabilities.

Sonic Analytics: A Basic Overview of Analytics

Analytics is about looking for patterns in data to help answer questions. Most businesses use analytics to help ensure more data-driven decision-making.

It is commonly said that, “All of the data that existed up to the past couple of years, is less data then we now generate every two days.” Being one of the world leaders in analytics, IBM has found that businesses that use analytics are twelve times more efficient and a third more profitable then ones that do not. *https://youtu.be/Zi8jTbXnamY

Walter, My Analytics Avatar

A Key Definition of Analytics is the discovery, interpretation, and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance. Analytics often favors data visualization to communicate insight.

The primary people responsible for conducting analytics on the massive amounts of data we have today are analysts. Analysts are skilled in using various technologies and methodologies to identify, inventory and integrate large amounts of data quickly.

Many Analysts today feel like they are drowning in a sea of data. They need to know how to take control of their data and analysis to quickly answer business questions and make critical decisions. They want to confidently present results and solutions to their managers, colleagues and clients.

The term analytics can often be used interchangeably with statistics and data science. What separates analytics from disciplines like statistics and data science is generally the speed of the analysis and the focus on solving business problems.

My goal with this series is to help you look at analytics in a way that will make data and analysis easier to understand and conduct.

My next training will be in June. Check out the details below:

https://www.sonicanalytics.com/events/data-analytics-3-0

05 Jun, 9:00 AM – 07 Jun, 5:00 PM
Discovery Suites Manila, Philippines, 25 ADB Ave, Ortigas Center, Pasig, 1600 Metro Manila, Philippines

Dan Meyer heads Sonic Analytics, an analytics training, consulting and outsourcing company with offices in Manila and the San Francisco Bay Area. With over 20 years in Big Data, Dan is one of the most sought after public speakers in Asia and has recently begun offering public training seminars in the United States.

We need to look at the data (analytics), plan a course of action (strategy) and share our data-driven viewpoints (presentation). So he has started an internship program under Sonic Analytics to empower the youth the use Analytic, plan Strategy and Present their views… ASP!

Sonic Analytics(www.sonicanalytics.com) brings big data analytics solutions like business intelligence, business dashboards and data storytelling to small and medium sized business looking to enhance their data-driven decision-making capabilities.

Data Analytics 3.0: A three-day intensive training on Data Analytics and Data Visualization

Data Analytics 3.0: Big Data Analytics, Data Value chain and Data Visualization on June 5-7, 2018 (9AM – 5PM) to be held at Discovery Suites, ADB Ave., Ortigas Center, Pasig. 

COURSE OVERVIEW:

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

Attendees will learn how to identify the right data, how data can be efficiently stored, then transformed into a friendly form for analysis, and finally how data analysis can yield insights.

This training will also 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, SQL and in depth learning of the tool “Tableau”, this is also 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.

 

KEY TOPICS: DAY ONE

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.
  • Discuss the Concept of Data Visualization.
  • Build A Business Dashboard Prototype.
  • Apply the key elements of Data Storytelling

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.

 

KEY TOPICS: DAY TWO

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.
  • Understand how data can be prepared for exceptional storytelling.

 

KEY TOPICS: DAY THREE 

At the end of this course, you will be able to:

  • Connect to your data.
  • Edit and save a data source.
  • Understand Tableau terminology.
  • Use the Tableau interface / paradigm to effectively create powerful visualizations.
  • Create basic calculations including basic arithmetic calculations, custom aggregations and ratios, date math, and quick table calculations.
  • Represent your data using the following visualization types:
  • Cross tabs
  • Geographic maps
  • Heat maps
  • Tree maps
  • Pie charts and bar charts
  • Dual axis and combined charts with different mark types
  • Highlight Tables
  • Scatter Plots
  • Build dashboards to share visualizations.

 

Tableau – Fundamentals

  • Introduction
  • Connecting to data
  • Simplifying and sorting your data
  • Organizing your data
  • Slicing your data by date
  • Using multiple measures in a view
  • Showing the relationship between numerical values
  • Mapping data geographically
  • Viewing specific values
  • Customizing your data
  • Analyzing data with quick table calculations
  • Showing breakdowns of the whole
  • Highlighting data with reference lines
  • Making your views available

 

Data Storytelling

Definition of a Data Storyteller. These experts are equally statistically minded and artistically gifted, with experience in programming and building data models that can be visualized and turned into data stories. Data Storytellers must have excellent communication and presentation skills that’s are used in translating data analyses into layman’s terms in order to influence a business decision or action. Their job is to ensure that the derived information is not only well researched and accurate, but also understandable and easily used to explain what the data says in a compelling way.

 

Overview of the Four Keys to Data Storytelling

  • Knowing your audience
  • Preparing your data
  • Choosing the right visual and designing it well
  • Telling the story

 

The Key Elements (D.R.A.P.S.) of Data Storytelling

  • Visualization is the fastest bandwidth channel for transferring high dimensional information into the human brain (Direct)
  • Visualization uncovers cause and effect relationships (Relationships)
  • Visualization grabs attention (Attention)
  • Visualization uncovers hidden patterns (Patterns)
  • Visualization separates data structure from data noise (Structure)

 

We only offer limited seats, register now at:  http://bit.ly/DataAnalyticsTraining30 or email us at info@sonicanalytics.com | marketing@sonicanalytics.com or call at (02) 968 1756

 

 

 

 

 

 

 

 

 

DMAIPH HR Analytics Strategy Lead

HR Analytics Strategy Lead

DMAIPH is an international analytics firm with offices in both the U.S. and the Philippines that specializes in providing analytics themed training, consulting and outsourcing to its clients.

DMAIPH also conducts analytics training classes facilitated by our President & Founder, Daniel Meyer. Mr. Meyer is an author, public speaker and one of the most sought after analytics experts in the Philippines. Over the past 5 years, Mr. Meyer has trained 1,000s of Filipinos on a variety of analytics topics. We are currently building out a marketing and analytics team to grow the training business line.

We currently employee over 60 employees here in the Philippines who are assigned to providing customer service, email support and graphic design work for a U.S. based client. This account is a mature account, having been established in 2013. This specific role will work directly with the marketing and analytics teams of DMAIPH and support the broader HR efforts for the other DMAIPH lines of business.

The role of the HR Analytics Strategy Lead has four primary functions;

  • 25% HR Generalist (Comp/Ben, Contracts, Recruitment, etc)
  • 25% HR Analytics Technical Trainer
  • 25% HR Analytics Projects
  • 25% HR Analytics Resource Speaker

Job Requirements:

  • At least 3 years of of HR work experience.
  • Experience in the BPO industry is a plus.
  • Four-year degree holder in an HR, related course preferred, but any undergraduate experience is acceptable.
  • Intermediate MS Excel skills.
  • A strong interest in analytics; using data to driven decision-making.
  • Experience with corporate training, public speaking and/or classroom teaching strongly preferred.
  • An Above average level of English proficiency.
  • A pleasant attitude and professional appearance.
  • A curious mind. Successful candidates will be able to demonstrate how they enjoy solving problems and looking for innovative solutions.

Job Duties:

HR Generalist (25%) – serving as an HR Generalist (Recruitment, Compensation & Benefits, and Employee Engagement) for a team of 10-15 marketing and analytics employees. Will also work with HR staff from DMAIPH business partners responsible for other DMAIPH teams.

HR Analytics Technical Trainer (25%) – will work alongside other DMAIPH trainers to deliver content specifically designed for HR Analytics training activities. Initially working with content already developed, over time the lead may develop their own content under the guidance of senior DMAIPH staff.

HR Analytics Projects (25%) – will work on ad hoc and ongoing analytics projects aligned with industry and academic needs to massively upskill HR staff. Will conduct research, prepare reports and deliver findings to DMAIPH management and key business partners.

HR Analytics Resource Speaker (25%) – will be assigned speaking roles at various academic and industry events where as needed. Content will be provided. Over time will become a spokesperson and champion for furthering the use of HR analytics in the Philippines.

Please note that we are not expecting successful candidates to already have work experience in all of these areas. There will be a large amount of training, coaching and mentoring to get the Talent Management Analyst up to speed. Above all else we are looking for someone who is curious, who is flexible and who can take initiative.

Compensation:

  • Starting salary depends on experience, but the position base is targeted at 30,000 PHP a month.
  • After probationary period, health benefits and paid leave will be made available (probation can last between 1 to 6 months).
  • Additional performance based incentives can be achieved for filling training classes and meeting HR metrics goals.
  • Up to P2,500 in tax-free allowances.
  • Possible 5-10% performance bonus upon normalization.
  • Complete 40 hours of work. This is a full-time job commitment.
  • Annual performance evaluation and compensation increases.
  • Standard employee benefits as mandated by Philippine law.
  • Company lap top and mobile phone may also be provided.

Location:

This position is primary office based, but will be able to work remotely a significant % of the time once past probationary status. There will be a need to go into the field to attend job fairs, DMAIPH training events and occasional conference and workshops. There may also be a need to report to our Ortigas office for meetings and trainings. During the onboarding and probationary period, the HR Analytics Strategy Lead may be required to come into the office regularly until they are fully up to speed.

Interested applicants please send your resume and contact details directly to me at danmeyer@dmaiph.com

The Data Analyst Era

FIRST THINGS FIRST,

 

https://www.sonicanalytics.com/

Do you think this is still the career era for nurses? The era of Physical Therapist?  The Networking era? The I.T eras? Why don’t you try to type in google right now and search Most in demand jobs in the futureand you will mostly find “Analyst” on every job description in demand in the future. The worst case is that you will also discover the worst job in the future, if you have been caught on that category. I say we are here to save you.

We are here to help you start building your future right now

 

https://www.facebook.com/pg/dmaiph/photos/?tab=album&album_id=1316439141834859And be the first one to learn and know what is in demand. We are here to supply you knowledge and provide you a strong foundation in analytics. We have the same curiosity when it comes to analytics? Trust me, I’m not a big fan of numbers, but I’m wrong, I never thought analytics also plays a role in giving us a perception through data visualization with the right purpose of using numbers. Not just some numbers you need to compute instructed by your professors to do so.

 

It’s all about numbers but.

It also equips with visualization with easy number to analyze. If you notice right now visualization plays an important role in our digital age today. Because we prefer to see imagery instead of computation, we prefer reading pictures instead reading books. Analytics have the same concept and there is a huge shortage of people who are skilled in working with data to answer questions to solve problems. Sonic Analytics

Therefore, you have seen the number of analyst job postings increasing at an amazing rate. Then why not apply it into our career, use this as an asset for you to innovate.

 

For those who are interested in or just beginning a career in data analysis,

here’s a few tips to help you get started,

Be willing to learn,

Being a sponge in learning data analysis (and with any field) can only reap the benefits. With data analysis, it’s important to start small and learn the basics and foundations before moving on and tackling bigger things. learning-picture.jpg

Building a solid foundation of education in the beginning helps you know the basics and allows you to work on building your skills and knowledge as you progress through your career.

 

Don’t be afraid to ask questions and get help

You can’t do it alone, and not seeing out help can cost you opportunities as you progress through your career. Reaching out isn’t a sign of defeat or being unknowledgeable, it shows that you’re passionate and want to learn more but need the proper guidance to get you there.images

Becoming a data analyst is a great career option for those who love to work with numbers with the right tools (We will guide you) to help you and to help companies, organizations draw conclusions and arm them with the information they need to make for decision making.

If you’re a beginner,

26993474_1325177484294358_3157857508557595202_nDon’t worry, we are here to teach you the important fundamentals of data analytics step by step in a layman’s term.

Now, it’s your big chance to participate in our upcoming trainings which focuses more on teaching young professionals like you.

 

DMAIPH is proud to present this 3-day Data Analytics training that covers different aspects of data identification, collection, storage, transformation, and analysis and involve hands-on use of common data management and analysis tools such as Excel, SQL and in depth learning of the tool “Tableau”, this is also designed for those with little to no prior experience with these tools.

Analytics Experts 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.

Attendees will learn how to identify the right data, how data can be efficiently stored, then transformed into a friendly form for analysis, and finally how data analysis can yield insights.

Come and Join Us!

Data Analytics 3.0

February 20 – 22 | 9:00am to 5:00pm

For inquiries: info@sonicanalytics.com | marketing@sonicanalytics.com

|  (02) 959 – 8017 | 0917-799-2827

 

Register Now!

DATA Analytics 3.0: Big Data, Data Value Chain and Data Visualization with Tableau – February 20-22, 2018

DMAIPH is proud to present this 3-day Data Analytics training that covers different aspects of data identification, collection, storage, transformation, and analysis and involve hands-on use of common data management and analysis tools such as Excel, SQL and in depth learning of the tool “Tableau”, this is also designed for those with little to no prior experience with these tools.

Analytics Experts 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.

Attendees will learn how to identify the right data, how data can be efficiently stored, then transformed into a friendly form for analysis, and finally how data analysis can yield insights.

 

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.

 

Continue reading “DATA Analytics 3.0: Big Data, Data Value Chain and Data Visualization with Tableau – February 20-22, 2018”

April 18 – Ortigas – Industry-Academe

Industry – Academe Data Science and Analytics Conference 2018

April 18, 2018
University of Asia and Pacific, Pearl Drive, Ortigas Center, Pasig City

The Analytics Association of the Philippines in partnership with DMAIPH and UA&P is proud to present the Industry – Academe Data Science and Analytics Conference 2018.

With the theme “Bridging the Industry-Academe Analytics Gap through the APEC Data Science and Analytics Competencies”, the conference aims to help academic institutions craft and deliver Analytics programs that are relevant, applied and experience-building for the students and to help the industry gain access to graduates ready for analytics jobs.

One of the highlights of the event is the dialogue between the industry and the academe where we will work to bridge the gap between the current syllabi and the Recommended APEC Data Science and Analytics Competencies developed through Project DARE (Data Analytics Raising Employment), an initiative led by the United States Department of Labor under APEC’s Human Resources Development Working Group and endorsed by the APEC Business Advisory Council.

Why Focus on APEC’s Data Science and Analytics Competencies?

Jobs requiring a familiarity with data analysis are forecasted to dramatically rise, resulting in a massive shortage of qualified employees. According to reports, some economies face a shortage of up to 1.5 million data analytics-enabled managers and analysts, costing billions of dollars in lost revenue annually. There is an urgent need to ensure that the future workforce is equipped with data analytics competencies to secure the jobs of tomorrow and move with ease in the labor market.

This is where Project DARE comes in. Project DARE aims to facilitate development of a data analytics-enabled workforce across the APEC region to effectively support sustainable economic growth and prosperity in the Asia-Pacific region. To do so, Project DARE developed a set of Recommended APEC Data Analytics Competencies which will be a resource to academic institutions and governments to align curricula, courses and programs so APEC economies are equipped to educate its workforce with the data analytics skills needed by employers in a data-driven future.

How was the Recommended Data Analytics Competencies Developed?

The Recommended APEC Data Analytics Competencies was developed through a public-private partnership with input from over 40 Advisory Group members comprised of distinguished business and higher education leaders who oversee data science and analytics needs for their organization and data science inter-disciplinary initiatives and curriculum. The Advisory Group was led by the private sector partner co- chairs, global skills and knowledge company Wiley and the Business Higher Education Forum (BHEF), with technical support by the EDISON (Education for Data Intensive Science to Open New Science Frontiers) Project. AAP’s Founding Members, Mr. Karlo Panti, Dr. Breda Quismorio, Mr. Sherwin Pelayo, Mr. Dan Meyer and Dr. Eugene Rex Jalao.

 

DMAI - Logo_ver2-02-01

Analytics Education – Facilitating a mastery of the fundamentals of analytics is what DMAIPH does best. As a key parnter of the Asia Pacific Economic Cooperation’s Project DARE initative, DMAIPH champions the use of using data. All across the world, companies are scrambling to hire analytics talent to optimize the big data they have in their businesses. We can empower students and their instructors with the knowledge they need to prepare for careers in data science and analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can set a guest lecturer date, On-the-Job Training experience or other analytics education solution specifically tailored to your needs.