Q12: Next please explain when and how we can use prescriptive analytics?

Prescriptive analytics goes one step further and finds the best course of action for a given situation. Its primary goal is to enhance decision-making by giving multiple outcomes based on multiple variables. The analogy of how doctors prescribe medicine to patients based on a wide range of variables in a patient’s health, using an equally wide range of treatment options.

“Prescriptive tells you the best way to get to where you want to be,” says Anne Robinson, director of supply chain analytics at Verizon Wireless and a past president of INFORMS, a society for analytics and operations research professionals. “If you want to differentiate yourself, the next step is the prescriptive tool box.

Predictive analytics answers the question what will happen. Prescriptive analytics not only anticipates what will happen and when it will happen, but also why it will happen. Further, prescriptive analytics suggests decision options on how to take advantage of a future opportunity or mitigate a future risk and shows the implication of each decision option.

Prescriptive analytics can continually take in new data to re-predict and re-prescribe, thus automatically improving prediction accuracy and prescribing better decision options. Prescriptive analytics allows us to handle blended data, a combination of structured (numbers, categories) and unstructured data (videos, images, sounds, texts), and business rules to predict what lies ahead. It also allows to take advantage of this predicted future without compromising other priorities.

In addition, most prescriptive analytics efforts require a predictive model with two additional components: actionable data and a feedback system that tracks the outcome produced by the action taken. It is simply too much data and too many outcomes to track if you haven’t invested in the right people and the right technology.

To really be impactful, this type of analytics also requires more data integration then the other types. “Data scientists typically spend about three-quarters of their time preparing data sets and only a quarter running analysis”, says Forrester Research analyst Mike Gualtieri. The need to not only blend and integrate data, but to constantly be looking at ways to keep the good and toss out the bad.

There is also a lot of discussion ongoing about the role prescriptive analytics actually replacing human decision-making. Advances in machine learning have gotten to a point where many routine business decisions can be made automatically.

We are currently seeing a lot of buzz in the industry about how far can an automated predictive analytics solution take us in freeing up time and resources. Currently we are finding ways to spend less time data blending and integrating and more analyzing and taking action. But soon it may be the whole analytics process that is managed by artificial intelligence.

Prescriptive analytics is the way of the future for those with the resources to apply it. However, for those who do not have those resources, prescriptive analytics is out of reach. This to me is a huge challenge for the analytics industry to solve.

The 3 Parts of Me: BPO Elite, DMAIPH and Sonic Analytics

A little about me. I oversee three small companies that specialize in analytics. I am not actively trying to sell you my services, but do hope that if you ever have a need for tailor made analytics solutions, you remember me.

BPO Elite is a consulting business that matches up companies in the U.S. with talent in the Philippines to do a variety of basic analytics and back office work. We DO NOT deal with companies looking just to send jobs overseas, focusing only on partners who need to add flexibility and depth to the talent pool. We have helped over a dozen companies find the right solution for their business to date.

DMAIPH is a company designed to deliver analytics training and support to colleges and universities looking to add more analytics centric courses and materials to their curriculum. To date, I have consulted with over a dozen of the top schools in the Philippines as well as working with student interns from UC Berkley, San Diego State and Diablo Valley College. My interns have helped a number of small business with basic analytics projects. I also blog about my love for analytics and how I teach it.

Sonic Analytics is a training business that focuses on corporate trainings in analytics related topics. Based on my experience as a senior analytics consultant with Wells Fargo Bank and in teaching analytics to college students in both the U.S. and the Philippines, I have come up with a very effective way to help professionals get a better handle on the analytics culture in their business. I have delivered trainings to thousands of people over the past few years, helping them learn how to make more data-driven decisions.

Each company represents one of the key components of my dream to bring better analytics to as many businesses as possible.

Prelude to Q10: Understanding the 3 different types of analytics.

The analytics efforts in a business are generally divided into 3 types; descriptive, predictive and prescriptive analytics.

A simple definition of descriptive analytics is that it is used to answer questions about what has happened in a business. It is primary use is to look at the current business situation with an eye towards looking for cause and effect. It helps one to understand how to manage in the present based on what happened in the past.

Per the Commission on Higher Education (CHED), descriptive analytics make use of current transactions to enable managers to visualize how the company is performing. When teaching the concept, it is generally focused on analysis and reporting to guide decision-making.

Most businesses use mostly descriptive analytics in their analysis, reporting and decision-making.

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Have to apologize to whoever made this image, I dont know the source, but you have my thanks for making it.

As you can see in the image, predictive analytics takes data and extrapolates patterns to predict likely outcomes. Past, Present, Past Present, Future… the goal being too provided educated guesses on what is most likely to happen next. The primary use of predictive analytics is to predict outcomes using models that will mitigate risk and eliminate choices based on unlikely outcomes.

Per CHED, Predictive analytics allows voluminous data to be used for prediction, classification and association making it very useful tool for projections, forecasts, and correlations. Most lessons around predictive analytics involve data modeling and require a much higher degree of skill then descriptive analytics.

In general, predictive analytics is used by large companies in data-rich industries. Up until recently there were very few tools available to smaller businesses to add this type of analytics to their decision-making.

Per CHED, Prescriptive Analytics help organizations develop insights to make decisions from the current data that maximizes the organization goals. Prescriptive analytics not only anticipates what will happen and when it will happen, but also why it will happen. Largely, instruction take the model building found in predictive analytics and supercharges it with more data, more choices and more outcomes.

Prescriptive analytics is fairly new and just now gaining widespread use in the corporate world. There are not many tools available that are cheap or easy to use. Generally, you find data scientists assigned to prescriptive analytics projects. It also take us closer to some decision-making in a business being completely automated. With enough data on hand, using machine learning to analyze the data, we are starting to see artificial intelligence at play with prescriptive analytics. It is a pretty exciting time.

Its important to keep in mind that to really be good at predictive and prescriptive analytics you need both the high tech tools and the training/experience to use them effectively.

Q9: Can you please describe the concepts of storing data in a data ware house?

Twenty years ago data was mostly stored in databases. These databases housed all the data a business would need to do analytics. Transaction data, sales data, customer data, demographic data was all neatly collected, stored and analyzed in databases.

A surprising number of companies still store most of their data in databases. It works well for business that just need to look at historical data to conduct basic descriptive analytics.

About ten years ago the amount of data captured in a business and the growing diversity in date sources and data storage brought about the mainstream use of data warehouses in the business world.

Data warehouse are often a collection of databases interconnected so that data can be brought together into one place for reporting and analysis.

Whether you are working with a data base or a data warehouse, you should have a basic understanding of how data is stored. It should be in table format, with header columns and data rows.

A good way to quickly assess the analytics culture of a business is to look at how data is shared among management. Does it look table like? Or is it obvious that most of the time spent by the author was put into decorating? If you can’t easy sort something, then you are not dealing with a good data culture.

The best way to have a good data culture is to have well documented data structures. Any dB admin worth a grain of salt has the data hierarchy mapped out and has a knowledge base to help users know what data is in each field.

Like with finding data, being good at storing data starts with knowing the environment. Any good analyst should have a basic understanding of how to use SQL to pull a query for a data table. Even if you cant do hard core coding, know how data is generally stored in a structure is key.

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Another important concept about data warehouses if you have to know how to join or blend data from different sources. When you have multiple data tables in a warehouse you often need to join the data on a common field. Data blending goes on step further as you are often trying to take data that doesn’t have a natural point on common that is easy to join on. Advanced data warehouses and data management tools can blend things easily, but its still important to understand the core concepts of how to join and blend data.

As I mentioned in earlier posts, there is now a new concept taking root that one up data warehouses. Data lakes are being used to address the fact that we have more unstructured data then we have structured data. Data bases and data warehouses were designed only to handle structured data the easily fits into a data able.

Now we have to collect data from images, videos, blogs, comments and other places that are not easily converted to a value. Data blending across both traditional structured data warehouses and new types of data is not easily done in most data warehouses so tools are being developed to bridge this gap.

The lake is no longer a place just to fish, but also to do all the other things a lake can be used for.

So, when it comes to understanding data warehouses, learn who built and/or maintains it and buy them a cup of coffee. Get your hands on the data dictionary, knowledge base, FAQ, metadata.. whatever you can to map out the data environment. If you do that then you can find use the big data stored in a data warehouse to find the right data at the right time.

Q8: Here’s something a lot of us are wondering, what exactly is big data?

Think about some of the things you do in your daily life. You get up, you eat, go to work/school, shop, do something for entertainment, bank, go online and do things on social media. Everything you do generates data. That data is captured in countless ways. And then its stored in countless places. And analyzed by countless numbers of people. And then used in countless ways by businesses to market, design, advertise, build, sell, and so on.

Every time you check your phone to see if there are any updates on Facebook you generate a lot of data for your phone manufacturer, your service provider and Facebook itself. Everything you like or comment on can be turned into a data point. The time, place and length of your connection all provide useful data. Get the point? Its endless.

That’s big data.

In general, big data is thought of as all the data businesses capture and store in a database that they can use for business decision-making.

When you think of data collections that have millions and millions of rows of data like big bank transaction data, or traffic data for major cities, or all the statistics captured everyday across professional sports. Way too much for man to analyze without help from technology. That’s all big data.

Every business defines its big data a little differently. There is no one way to look at how best to manage big data because big data is such a living, evolving, never ending flow of information. It’s like lakes of water that are too big to swim across and too deep to dive to the bottom of without help. And no two lakes are alike.

Data analysts and data scientists are the ones who know the lake and guide you across or build you a submarine to explore the bottom.

As I have mentioned in previous posts, knowing the data environment is key to your success. And big data just adds weight to that statement. If you don’t know where all the data is coming from, can’t be sure if its clean, then you will get lost in the deluge of big data.

The Fundamental of Business Analytics – Business Analytics is the application of talent, technology and technique on business data for the purpose of extracting insights and discovering opportunities.

DMAIPH specializes in empowering organizations, schools, and businesses with a mastery of the fundamentals of business analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out how you can strengthen your business analytics fundamentals.

Q7: What exactly is data science and why the rapid rise of data scientists?

A year ago I might have found it challenging to really answer this question. The first time I had heard of the term data science and a data scientist wasn’t that long ago. And I have been doing some pretty advanced analytics for close to 20 years now. I know the term has been around in academic and research circles awhile longer, but 2014 is the first time I ever saw a job posting for data scientist in big business.

So what is data science? Besides simply being the study of data, it generally refers to using complex models, machine learning, predictive and prescriptive analytics and powerful technology to analyze business data in much greater volume, velocity and variety then possible a few years ago.

And of course the ones charged with doing the data science are data scientists. They understand math, statistics, and theories that can be applied to business data using new technologies and methodologies.

The biggest challenge to being a true data scientist is that you have to be adapt at both technology and working with people. Being a business data expert, knowing how to code and doing higher math are only half the job. You have to also share your data, communicate it in ways that drive action, share and engage with non-data centric people. It’s hard to find people who are good at both.

Image from Forbes Magazine.

In addition, whole some data scientists are educated to be data scientists, very, very few actually have any kind of degree in data science. That kind of degree really didn’t exist until very recently. Instead most data scientists have advanced degrees is related subjects and have migrated into the business world do to market demand.

That demand has been growing at a staggering rate the past few years as every day we generate more and more data across the planet. President Obama first employed a data scientist for his campaign in 2012. The White House now has a chief data scientist position.

If you were to compare results from job board searches form 2012, you’d see maybe 100 data scientist job postings. Now its easily in the 1000’s. So that’s why the job market for data scientist is one of the hottest around. Lack of training programs, having both tech and people skills, and the booming demand due to unending new data to being analyzed.

Some people ask me if I’m a data scientist I am careful with my answer. True data science is not something I am academically prepared for nor I have never published anything in a scholarly journal. But my real world experience working with data has made me an expert on many aspects of data science.

I guess I feel more like an analyst, but a freakin awesome analyst who can do a lot of things using data that are super important to a business.

Analytics Education – Facilitating a mastery of the fundamentals of analytics is what DMAIPH does best. As a key parnter of the Data Science Philippines Meetup Group, 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 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.

Q4: Can you please describe the current state of analytics in the Philippines? – Part 1

Let me tackle this question in two parts. The history major in me demands we look at how we got to where we are now before we talk too much about where we are going.

To start, both the appreciation for and the use of analytics has grown tremendously over the past few years. When I first started thinking about setting up a business in the Philippines back in 2011, hardly anyone knew much about analytics. Big banks, large call centers, multinational corporations and only the top schools were even talking the concept.

It was a challenge to fill my initial training classes due to lack of general awareness. Even at industry events and conferences it was rare to hear much about the idea of using data to drive business decisions.

Doing a search on the top job board in the Philippines back in 2012 for the jobs with analyst in the title netted about 1,000 job postings on any given day. The average salary was some here around 30,000 PHP a month. It was a challenge to find good talent and those who could do analytics were all gainfully employed.

It wasn’t until 2013 that I stated seeing other analytics training options and those were just ones being done by IBM to meet the CHED (Commission on Higher Education) requiring the implementation of a six class elective tract in business analytics. The was accompanied by the launching of Analytica, and IBM backed effort to push the Philippines towards being more a viable option for analytics outsourcing.

At this time a job search for analyst would bring back about 1,500 jobs. Salaries were starting to rise for analysts as well with the market average getting closer to 50,000 PHP. Still not a lot of public training or analytics centric organizations around then.

About the same time I started getting invited to schools on a regular basis to lecture about analytics to IT, CompSci and Management students. For the most part they had no idea of the career opportunities out there for those with analytics talent. I consulted with several schools on how to implement the CHED memo and how to prepare their students for analytics careers.

In 2014, an analyst job search was yielding closer 2,000 open jobs. The average salary climbed north of 50,000 Pesos for an experience analyst. I did a lot more trainings, being able to routinely fill a class of people hungry to learn more about analytics and how it could help them in their jobs.

The most in demand analytics skills up to this point where many centered on management reporting, production analysis and workforce management. Most analysts used some kind on proprietary database to store data and did just about all their analysis in Excel.

By 2015, analytics was finally in the mainstream. Job posting now routinely called for specific skills sets in programming languages and business intelligence tools. Multiple organizations made up of analytics professionals started coming together. The number of jobs open hit 2,500 on any given day and salaries for really good analysts hit 70,000 PHP a year. By this time, many outsourcing companies focused on setting up team of analysts to offer analytics as an outsourcing option. Big data jobs and even data scientist positions started showing up in large numbers.

So here, we are now in early 2016. The sky is the limit when it comes to Filipinos with analytics talent being able to enjoy good career growth and make substantial salaries. The schools are now starting to churn out talent with analytics careers in mind. Things look great on the supply side of analytics talent and the market growth opportunity for businesses offering analytics is huge.

An additional complexity in the analytics world is the vast number of tools out there to gather, store, analyze and present data. Although IBM is by far the biggest player in training people, they are not the universal solution when it comes to the methodologies and technologies people use every day.

The biggest challenge today is that the demand for analytic talent dwarves the actual current and near term talent supply. The global need for not just analysts, but also data scientists has quickened to a point where catching up for the Philippines seems almost impossible.

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HR & Recruitment Analytics is the application of talent, technology and technique on business data for the purpose of extracting insights and discovering opportunities. DMAIPH specializes in empowering organizations, schools, and businesses with a mastery of the fundamentals of business analytics.

The recruitment and retention of top talent is the biggest challenge facing just about every organization. You really have to Think Through The Box to come up with winning solutions to effectively attract, retain and manage talent in the Philippines today. DMAIPH is a leading expert in empowering HR & Recruitment teams with analytics techniques to optimize their talent acquisition and management processes.

Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to learn how to get more analytics in your HR & Recruitment process so you can rise to the top in the ever quickening demand for top talent.

Q1: To start can you provide us with a basic overview of what is analytics?

Analytics is simply about looking for patterns in data to help answer questions. Most people use analytics within a business to help ensure more data-driven decision making. Businesses that use analytics are generally much more efficient and much more profitable then ones that don’t.

Analytics is generally employed by analysts who are skilled in using certain technologies and methodologies to identify, inventory and integrate large amounts of data quickly. What separates analytics from statistics and data science is generally the speed of the analysis and the focus on solving business problems.

The most common form of analytics is general business analytics that are 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. However, analytics can be used in an almost limitless number of business functions in specific areas like HR, recruitment, marketing, finance, and so on.

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. As a result, there is a huge shortage of people who are skilled in working with data to answer questions and solve problems. This why you have seen the number of analyst job postings increasing at an amazing rate.

If you 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.

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The Fundamental of Business Analytics – Business Analytics is the application of talent, technology and technique on business data for the purpose of extrating inights and discovering opportuniites. DMAIPH specializes in empowering organizations, schools, and busiensses with a mastery of the fundamentals of business analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out how you can strengthen your business analytics fundamentals.

DMAIPH and Sonic Analytics is looking for a Marketing Analyst/Administrative Assistant

http://www.sonicanalytics.com/

Sonic Analytics is an analytics-centric consulting, outsourcing and training company with teams in the United States and the Philippines. We specialize in corporate analytics consulting, public analytics training and small and medium business analytics outsourcing. We maintain an office in Ortigas, Pasig City.

We are seeking an Administrative Assistant, which is a full-time entry-level business operations position. The position is predominately office based, working out of our Oritgas location. We are looking for a flexible, hard-working and analytics minded individual to take on the following tasks:

Prepare Monthly Ledger
Meet with book keeper for tax reporting once a month
Safe keep Permits, Government Certificates, Receipts and other business documents if needed
Update expense and income trackers
Act as a POC for any analytics seminar/service related inquiries
Provide guidance to interns/OJT
Help develop an effective marketing campaign
Attend events on behalf of Sonic Analytics
Assist with setting-up public and in-house seminars
Assist with Payroll

Successful candidates need to meet the following requirements:

Previous work experience working in an office environment and/or customer service.
Familiar with MS Office, particularly MS Excel.
Basic understanding of business analytics and using data to solve problems.
Strong internet research skills and knowledge of social media.
Strong communication and organizational skills
Self-motivated and a willingness to learn
Above average written and conversational English.
A bank account with BPI or the ability to open a bank account

Basic compensation: Base monthly salary is P12,000.

– Up to P2,500 in tax-free allowances.
– 5-10% performance bonus upon normalization.
– Complete 40 hours of work. This is a full-time job commitment.
– Regular Hours are 9:30am-6pm, Monday to Friday.
– Annual performance evaluation and compensation increases.
– Standard employee benefits as mandated by Philippine law.

Interested candidates should send their most recent resume to jen.ifer@sonicanalytics.com for consideration.

Analytics Jobs – Sonic Analytics in partnership with DMAIPH; hires, refers and connects Filipino analytics talent. The Philippines is at the center of the action when it comes to solutions to the global need for analytics. Working with DMAIPH to find work, hire analytics talent or set up analytics teams will ensure you are tapped into the best of the best when it comes to analytics in the Philippines. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out how to take advantage of this booming opportunity.

Implementing the CHED Memo on Business Analytics > How DMAIPH Can Help

In 2013, the Commission for Higher Education (CHED), the governing body for Higher Education in the Philippines, published a memorandum requiring accredited colleges and universities to establish a Business Analytics Specialization Program for Business Admin and IT students.

The objectives of the business analytics specialization track aims to provide Filipino students the skills needed for different forms of Analytics namely, Descriptive, Predictive and Prescriptive Analytics. This track enables students to identify opportunities and implement or enact solutions for which these analytics can be used to solve business problems to aid intelligence and informed business decision-making.

One of the analytics training solutions that DMAIPH offers, is partnering with schools on curriculum and instruction enhancement. We are also more than willing to meet with you to explore possibilities of collaboration.

The key areas DMAIPH can assist with are as follows:

Consultation with Key School Administration Decision Makers
Initial Faculty Training via a 1-Day hands on workshop
Building Student Awareness by speaking at student events
Guest Speaking in classrooms and academic events
OJT Opportunities with DMAI and out partner companies
Fresh Grad Training for analysts looking to start their career
Provide a textbook for business analytics based on the CHED memo

DMAIPH is adapt at providing staff and students with an overview of the current trends in business analytics that drives today’s businesses, as well as providing an understanding on data management techniques that can help organizations achieve their business goals and address operational challenges.

The need for more analysts and professionals with analytics training in the Philippines continues to quicken at an amazing rate. On any given day you can see over 2,000 analyst jobs posted on jobstreet.com

The demand of analytics talent in the Philippines far outweighs the demand. Even with specialized tracks like the Fundamentals of Business Analytics starting up over the Philippines, more needs to be done.

DMAIPH is uniquely positioned to help schools deliver on CHED’s memo and help supply the demand Filipino businesses, BPOs and Call Centers are asking for.

We have been doing analytics training, consulting and outsourcing in the Philippines since May 2012. In addition, DMAIPH has helped over two dozen companies bring more analytics into their business and have trained over 100 batches of analytics trainees.

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 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.

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