Category: Analytics Education

A Beginner’s 7-Step Guide to Data Analytics

Data analytics is a powerful tool that allows us to extract valuable insights from vast amounts of data. Whether you’re a beginner or looking to enhance your skills, this simple how-to guide will help you navigate the world of data analytics. By following these steps, you’ll be well on your way to unlocking the potential of data and making informed decisions.

Step 1: Define Your Objective

Start by clearly defining your objective. What question or problem are you trying to address? By having a clear goal in mind, you can focus your efforts and select the right data and analytical techniques to achieve your desired outcome.

Step 2: Gather Relevant Data

Identify and gather the relevant data for your analysis. This may involve collecting data from various sources, such as databases, spreadsheets, or online platforms. Ensure that the data you collect is accurate, complete, and aligned with your objective.

Step 3: Clean and Prepare Your Data

Data cleaning and preparation are crucial steps in the data analytics process. Remove any duplicates, handle missing values, and correct errors or inconsistencies in the data. Additionally, transform the data into a format suitable for analysis, such as structured tables or organized datasets.

Step 4: Choose the Right Analytical Techniques

Select the appropriate analytical techniques based on your objective and the nature of your data. This may include descriptive analytics (summarizing and visualizing data), diagnostic analytics (exploring relationships and patterns), predictive analytics (making forecasts or predictions), or prescriptive analytics (providing recommendations or decision support).

Step 5: Apply the Chosen Techniques

Apply the selected analytical techniques to your prepared data. Utilize software or programming languages specifically designed for data analytics, such as Python or R. Explore the data, perform calculations, run statistical analyses, and generate visualizations to uncover insights and patterns.

Step 6: Interpret and Communicate Your Findings

Interpret the results of your analysis and extract meaningful insights. What do the patterns and trends in the data tell you? Communicate your findings in a clear and concise manner, using visualizations, charts, or reports to present the information effectively. Tailor your communication to the intended audience, whether they are technical or non-technical stakeholders.

Step 7: Take Action and Iterate

Based on the insights gained from your analysis, take action and make informed decisions. Monitor the outcomes of your decisions and evaluate their impact. Iterate and refine your analysis as needed, incorporating new data or adjusting your techniques to improve accuracy and effectiveness.

Data analytics is a valuable skill that empowers individuals and organizations to harness the power of data. By following this beginner’s guide, you can embark on your data analytics journey with confidence. With practice and continuous learning, you’ll unlock the potential of data and make data-driven decisions that drive success and innovation.

Get ahead of the competition by learning from one of the best in the industry. Book Daniel Meyer for a speaking engagement in your company and start improving your data analytics skills now.

Daniel Meyer is the head of Sonic Analytics, an analytics firm that has been in the Big Data industry for over 20 years and has offices in Manila, the San Francisco Bay Area, and Ocala, Florida. He is an accomplished author, public speaker, and business expert specializing in virtual staffing and process automation.

Dan is known for providing big data analytics solutions, including business intelligence and data storytelling, to small businesses seeking to improve their use of data, virtual staffing, and technology. He strongly believes in using analytics for civic responsibility, and offers training, consulting, and education to promote this advocacy.

With his experience in training over 10,000 Filipinos, Dan is passionate about empowering the youth with valuable skills, such as graphic design, video editing, and data analytics. His objective is to equip them with the necessary abilities to harness the dynamic employment opportunities that lay ahead for millions of Filipinos.

Data Science Dos and Don’ts: Navigating Common Pitfalls 

Data science has become a cornerstone of decision-making and innovation across industries. As the demand for skilled data scientists continues to soar, it’s essential to navigate this field with precision and avoid common pitfalls. 

Below are some of the most common mistakes made in the data science industry coupled with valuable insights on how to sidestep them. By understanding these pitfalls and adopting best practices, you can elevate your data science journey and maximize your chances of success.

  1. Neglecting Problem Formulation

One of the biggest mistakes in data science is rushing into analysis without a clear problem formulation. Failing to define the problem properly can lead to wasted time and effort. Ensure you understand the problem statement, its business implications, and the expected outcomes before diving into data analysis.

To avoid this mistake, Invest sufficient time in problem formulation. Collaborate with stakeholders, ask questions, and align your analysis with the business objectives. Clearly define the problem statement and set measurable goals to guide your data science efforts effectively.

  1. Insufficient Data Cleaning and Preprocessing

Data cleaning and preprocessing are often overlooked, yet they are critical for accurate insights. Neglecting these steps can introduce bias, errors, and anomalies into your analysis, leading to flawed conclusions.

A simple solution to this is to dedicate ample time to data cleaning and preprocessing. Handle missing values, address outliers, standardize data formats, and normalize variables. Use exploratory data analysis techniques to uncover patterns and ensure data quality before proceeding with analysis.

  1. Lack of Communication and Collaboration

Data science is not a solitary endeavor; it requires collaboration and effective communication with stakeholders, domain experts, and fellow data scientists. Failing to communicate findings, assumptions, and limitations can hinder project success and undermine the value of your work.

Foster open communication channels and actively engage with stakeholders. Clearly communicate your findings, methodologies, and uncertainties in a way that is easily understood by both technical and non-technical audiences. Seek feedback and incorporate domain expertise throughout the project lifecycle.

  1. Ignoring Ethical Considerations

In an era of increasing data privacy concerns, overlooking ethical considerations can have severe consequences. Ignoring privacy regulations, handling sensitive data improperly, or allowing biases to creep into your models can damage trust and reputation.

Always prioritize ethics and privacy throughout the data science process. Understand and comply with relevant regulations. Be aware of potential biases in your data and algorithms and take steps to mitigate them. Strive for transparency and accountability in your analysis.

Data science offers immense opportunities, but it’s important to avoid common mistakes that can derail your efforts. Continuously learn, adapt, and collaborate with others in the field. Embrace best practices, foster a growth mindset, and aim for excellence. By sidestepping these common mistakes, you’ll be well on your way to becoming a successful data scientist, making meaningful contributions in the ever-evolving world of data science.

Don’t miss out on our content, make sure to follow our page!

Daniel Meyer is the head of Sonic Analytics, an analytics firm that has been in the Big Data industry for over 20 years and has offices in Manila, the San Francisco Bay Area, and Ocala, Florida. He is an accomplished author, public speaker, and business expert specializing in virtual staffing and process automation.

Dan is known for providing big data analytics solutions, including business intelligence and data storytelling, to small businesses seeking to improve their use of data, virtual staffing, and technology. He strongly believes in using analytics for civic responsibility, and offers training, consulting, and education to promote this advocacy.

With his experience in training over 10,000 Filipinos, Dan is passionate about empowering the youth with valuable skills, such as graphic design, video editing, and data analytics. His objective is to equip them with the necessary abilities to harness the dynamic employment opportunities that lay ahead for millions of Filipinos.

10 Essential Tips for Success in the Data Science Industry

In the world of data science, the power of information unlocks countless opportunities. In this fast-paced industry, success comes to those who are well-equipped with the right skills, knowledge, and mindset. 

Whether you’re an aspiring data scientist or looking to level up your existing skills, we’ve got you covered. From mastering technical expertise to nurturing soft skills, these tips will guide you on your journey toward becoming a data science superstar.

  1. Continuously Learn and Stay Curious. Data science is a rapidly evolving field, so make it a priority to stay updated with the latest advancements, techniques, and tools. Engage in lifelong learning through online courses, webinars, conferences, and reading industry publications.
  1. Master the Fundamentals. Develop a strong foundation in statistics, mathematics, and programming languages such as Python or R. Understanding the fundamentals will enable you to tackle complex data problems with confidence.
  1. Sharpen Your Coding Skills. Proficiency in programming languages is crucial for data scientists. Regularly practice coding to enhance your skills in data manipulation, analysis, and visualization. Collaborate on coding projects or participate in coding competitions to further improve your abilities.
  1. Hone Your Analytical Skills. Data scientists need to think critically and approach problems analytically. Continuously work on enhancing your analytical skills by solving challenging problems, participating in Kaggle competitions, or working on real-world projects.
  1. Build a Solid Foundation in Mathematics and Statistics. A strong grasp of mathematical concepts and statistical techniques is essential for data science. Understand concepts such as linear algebra, probability, hypothesis testing, regression, and clustering, as they form the backbone of data analysis.

6. Develop Strong Communication Skills. Data scientists must effectively communicate their findings to both technical and non-technical stakeholders. Practice translating complex concepts into simple, understandable terms. Develop visual storytelling skills to present data insights in a compelling manner.

7. Embrace Collaborative Work. Data science is rarely a solitary pursuit. Collaborate with peers, join data science communities, and participate in open-source projects. Engaging in collaborative work will expose you to diverse perspectives and help you grow as a data scientist.

    8. Gain Domain Knowledge. Specialize in an industry or domain of interest to become a valuable asset. Acquire domain-specific knowledge to better understand the context of the data you’ll be working with. This will allow you to derive more meaningful insights and make better data-driven decisions.

    9. Stay Ethical and Mindful of Privacy. As a data scientist, you have access to sensitive information. Adhere to ethical practices, respect privacy regulations, and prioritize data security. Handle data responsibly and ensure transparency in your work.

    10. Cultivate a Problem-Solving Mindset. Approach every data science problem as an opportunity to learn and grow. Be persistent, patient, and open to experimentation. Embrace challenges and view setbacks as valuable learning experiences. A problem-solving mindset is crucial for success in the data science industry.

    Remember, success in data science is a continuous journey of learning, exploring, and adapting. Embrace challenges, stay curious, and always strive for growth. With a strong foundation in technical skills, coupled with effective communication, problem-solving abilities, and ethical practices, you’re equipped to make a lasting impact in the world of data science. 

    Get ahead of the competition by learning from one of the best in the industry. Book Daniel Meyer for a speaking engagement in your company and start improving your data analytics skills now.

    Daniel Meyer is the head of Sonic Analytics, an analytics firm that has been in the Big Data industry for over 20 years and has offices in Manila, the San Francisco Bay Area, and Ocala, Florida. He is an accomplished author, public speaker, and business expert specializing in virtual staffing and process automation.

    Dan is known for providing big data analytics solutions, including business intelligence and data storytelling, to small businesses seeking to improve their use of data, virtual staffing, and technology. He strongly believes in using analytics for civic responsibility, and offers training, consulting, and education to promote this advocacy.

    With his experience in training over 10,000 Filipinos, Dan is passionate about empowering the youth with valuable skills, such as graphic design, video editing, and data analytics. His objective is to equip them with the necessary abilities to harness the dynamic employment opportunities that lay ahead for millions of Filipinos

    Bridging the Data Science Gap: Where to Study in the Philippines

    With the growing amount of data and rising demand for data professionals in the Philippines, some of the most prominent universities in the country have started offering degree programs and specialized courses to provide professionals with additional skills to take on a career in Data Science. 

    University of the Philippines – Diliman

    The University of the Philippines – Diliman offers a Professional Master in Data Science (Analytics) program that equips professionals with a solid foundation in statistical science and proficiency in statistical machine learning to solve real-world problems.

    Ateneo de Manila University

    In partnership with the Queen Mary University of London, Ateneo de Manila University offers a Master of Science in Data Science program, which lasts 18 – 21 months. Students may spend a semester in London, and the credits earned abroad will still be part of the Ateneo degree.

    University of Santo Tomas

    The University of Santo Tomas offers a Bachelor of Science in Data Science program that covers a wide range of topics, including programming, machine learning, and data visualization. Students have the opportunity to participate in internships and capstone projects to gain real-world experience in solving data-related problems.

    University of Asia and the Pacific

    The UA&P offers a Bachelor’s Degree in Data Science and a part-time Master’s Degree in Applied Business Analytics to address the shortage of data specialists in the Philippines. Both programs aim to equip students with skills and practical experience to deal with real-world problems while being guided by professors with relevant and globally competent qualifications in the field.

    De La Salle University

    DLSU offers a Minor in Data Science program, aiming to equip students with basic working knowledge in statistics. DLSU also offers 40-hour diploma courses relevant to the field, such as Foundation of Data Science and Machine Learning, to boost the skills and qualifications of professionals in various fields to take on more promising Data-Science-related positions in their respective industries.

    Asian Institute of Management (AIM)

    AIM’s Master’s program is a 14-month program designed to train specialists who are skilled in machine and deep learning, data mining, and analytics. AIM also offers a doctoral program in data science – the first in the Philippines and only one of few in Asia.

    Technological Institute of the Philippines (TIP)

    TIP offers a Professional Science Master’s Degree in Data Science (PSMDS), which aims to develop professionals who have the ability to lead their organizations in using data aid in the growth of their industries.

    Mapua University

    Mapua University offers an undergraduate program in Data Science, providing students with the skills and knowledge necessary to become professional data scientists working in various industries.

    Cosmopoint International Institute of Technology (CIIT) 

    CIIT provides a specialist course for those interested in data science. The specialist course lasts for only three months and engages students in different software essential for any would-be Data Science Specialists.

    University of Science and Technology of Southern Philippines (USTP)

    The University of Science and Technology of Southern Philippines (USTP)’s Bachelor of Science in Data Science (BSDS) program was developed to produce graduates who are competent in various fields of data science, such as data management, data analytics, and data visualization.

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    Daniel Meyer is the head of Sonic Analytics, an analytics firm that has been in the Big Data industry for over 20 years and has offices in Manila, the San Francisco Bay Area, and Ocala, Florida. He is an accomplished author, public speaker, and business expert specializing in virtual staffing and process automation.

    Dan is known for providing big data analytics solutions, including business intelligence and data storytelling, to small businesses seeking to improve their use of data, virtual staffing, and technology. He strongly believes in using analytics for civic responsibility, and offers training, consulting, and education to promote this advocacy.

    With his experience in training over 10,000 Filipinos, Dan is passionate about empowering the youth with valuable skills, such as graphic design, video editing, and data analytics. His objective is to equip them with the necessary abilities to harness the dynamic employment opportunities that lay ahead for millions of Filipinos.

    Data will talk to you if you’re willing to listen.

    Data is not just a collection of numbers and statistics – it has a story to tell. By analyzing data and paying attention to the patterns and trends, you can gain a deeper understanding of your business, customers, and industry. However, this requires an open mind and a willingness to listen. It’s not enough to simply collect data and store it away – you have to actively engage with it in order to unlock its full potential. So the next time you’re working with data, remember to listen closely – it just might reveal something you never expected.

    Daniel Meyer is the head of Sonic Analytics, an analytics firm that has been in the Big Data industry for over 20 years and has offices in Manila, the San Francisco Bay Area, and Ocala, Florida. He is an accomplished author, public speaker, and business expert specializing in virtual staffing and process automation.

    Dan is known for providing big data analytics solutions, including business intelligence and data storytelling, to small businesses seeking to improve their use of data, virtual staffing, and technology. He strongly believes in using analytics for civic responsibility, and offers training, consulting, and education to promote this advocacy.

    With his experience in training over 10,000 Filipinos, Dan is passionate about empowering the youth with valuable skills, such as graphic design, video editing, and data analytics. His objective is to equip them with the necessary abilities to harness the dynamic employment opportunities that lay ahead for millions of Filipinos.

    Decoding Data Science: A Useful Guide to Basic Terminology (Part 1)

    Are you new to the world of data science and feeling a little overwhelmed by all the jargon and technical terms? Don’t worry, we’ve got you covered! In this 2-part series, we’ll be breaking down the basics of data science terminology to make it easy and accessible for everyone.

    Today, we’ll be exploring five key terms that are essential to building a solid foundation in data science.

    1. Data Science

    The field of combining programming, mathematics, and statistics to analyze data and provide insights for decision making and problem solving. Data Scientists have high-level technical skills and use various programming languages to collect, interpret, format, model, predict, and manipulate data.

    1. Algorithm

    A set of repeatable instructions, usually expressed mathematically, used to process data. Algorithms can be constructed by humans or machines and adjusted until the desired result is achieved. Machines are now commonly used due to advancements in Artificial Intelligence.

    1. Data Analytics 

    The process of using existing information to answer questions for better business decision-making. It involves continuous collection and analysis of data, with a focus on ensuring data integrity and accurate evaluation of research results.

    1. Data Mining 

    The process of sorting large data sets to identify patterns and relationships that can help solve business problems. It is a component of Data Analysis and one of the core disciplines of Data Science. Data mining techniques and tools can be used to predict future trends and make more informed business decisions.

    1. Big Data 

    A term used for data that is too large and complex for traditional data management tools to store and process efficiently. Big Data can provide more complete and precise answers by confirming information from multiple data sources.

    Understanding these key terms is essential for anyone looking to get started in data science. Stay tuned next week as we continue to explore key concepts and terminology in data science.

    Don’t miss out on our content, make sure to follow our page!

    Daniel Meyer is the head of Sonic Analytics, an analytics firm that has been in the Big Data industry for over 20 years and has offices in Manila, the San Francisco Bay Area, and Ocala, Florida. He is an accomplished author, public speaker, and business expert specializing in virtual staffing and process automation.

    Dan is known for providing big data analytics solutions, including business intelligence and data storytelling, to small businesses seeking to improve their use of data, virtual staffing, and technology. He strongly believes in using analytics for civic responsibility, and offers training, consulting, and education to promote this advocacy.

    With his experience in training over 10,000 Filipinos, Dan is passionate about empowering the youth with valuable skills, such as graphic design, video editing, and data analytics. His objective is to equip them with the necessary abilities to harness the dynamic employment opportunities that lay ahead for millions of Filipinos.

    Data Analytics in the Philippines: Unlocking Unlimited Potential

    In recent years, the Philippines has seen a growing interest in data analytics, with organizations and companies investing in this field to improve their decision-making processes and gain a competitive edge. This trend is especially clear in the finance, healthcare, and e-commerce industries, where data analytics has become an essential tool for success.

    The Philippine government has also recognized the importance of data analytics and has taken steps to promote its use. The Department of Science and Technology (DOST) and the Technical Education and Skills Development Authority (TESDA) have started to offer free online training courses for data analysts to fix the skills mismatch and shortage that has been seen in this field. This training is intended to cater to unemployed individuals, including high school graduates, and equip them with the necessary skills to enter the job market.

    The Analytics Association of the Philippines estimates that by 2028, the country will need 500,000 analytics professionals. This need is not just in the IT field; data analysts are also needed in many other business fields. The entry-level salary for data analysts in the Philippines can go as high as P25,000 per month, making it an attractive career option for many.

    To meet the demand for skilled professionals in this field, universities in the Philippines are starting to offer courses and degree programs in data analytics. The University of the Philippines Diliman has a Master of Science in Data Science program, while Ateneo de Manila University has a Bachelor of Science in Data Science program. This move by universities is important for making sure that the Philippines has enough skilled workers to meet the growing demand for data analysts.

    It is also important for companies and organizations to talk to people in the industry to find out what skills are needed for jobs. As Sherwin Pelayo, executive director of the Analytics Association of the Philippines, said, “We talked to our industry members, and they said that if these skills were taught in senior high school, we would hire those who possess them.” The executive director of Philippine Business for Education, Justine Raagas, agreed with this point of view and stressed the need to talk to these sectors because they know what is needed in the workplace.

    The Department of Trade and Industry has also emphasized the importance of knowing the skill sets needed by companies and training people based on these needs to ensure their employability after graduation. This approach ensures that individuals are equipped with the necessary skills that are in demand in the job market.

    In conclusion, the Philippines is slowly but steadily embracing data analytics, and we can expect more changes and improvements in this field in the coming years. The government, universities, and private sector must continue to work together to make sure that the workforce has the skills it needs to meet the growing demand for data analysts. By doing so, the Philippines can position itself as a hub for data analytics in the region, and its workforce can contribute to the country’s economic growth and development.

    Don’t miss out on more of Dan’s expert content. Follow his social media channels for exclusive tips, insights, and valuable information on data science and analytics.

    Daniel Meyer is the head of Sonic Analytics, an analytics firm that has been in the Big Data industry for over 20 years and has offices in Manila, the San Francisco Bay Area, and Ocala, Florida. He is an accomplished author, public speaker, and business expert specializing in virtual staffing and process automation.

    Dan is known for providing big data analytics solutions, including business intelligence and data storytelling, to small businesses seeking to improve their use of data, virtual staffing, and technology. He strongly believes in using analytics for civic responsibility, and offers training, consulting, and education to promote this advocacy.

    With his experience in training over 10,000 Filipinos, Dan is passionate about empowering the youth with valuable skills, such as graphic design, video editing, and data analytics. His objective is to equip them with the necessary abilities to harness the dynamic employment opportunities that lay ahead for millions of Filipinos.

    What Makes Being a Virtual Assistant with Sonic Analytics Special

    It’s funny how this all started.

    Eight years ago, I had moved to the Philippines to set up an analytics training company. It took a few years, but we were quite successful in becoming THE name brand in analytics training in not just the Philippines but across Southeast Asia.

    While in the midst of getting the business established, I got a request from a friend of a friend to help them do some outsourcing. Specifically, the requirement was to set up a team of six SEO keywording specialists to tag images on an online auction site. I shook my network and we quickly set up the team and they dove in.

    We were so successful that we quickly expanded the team to 12, added a graphic designer and an e-mail marketer. All home-based workers. The client was so happy, we just kept adding. To the point where we quickly had over 30 employees on the account.

    There were two things we did that made a difference. So much of a difference that are attrition has been under 10% year of year ever since. In the outsourcing industry, that is unheard of. And for home-based work, where most people work as freelancers, the “ghosting” rate is so high that it’s basically a 50/50 craps shoot if you get a good person.

    So, the first of the two difference makes is the talent pool. This is true of VAs as whole, but for me it’s my secret sauce. Most of my employees, and just about all of the leadership team are stay at home moms who used to work in the call center industry. They have good English; they have worked within an American business model and they are used to structure. They also have a big incentive to work hard to provide for the family and be there every day for their kids.

    The other big difference? You may have noticed I refer to my team as employees. They are exactly that. Most VA services that are work from home jobs can be kinda shady. Low paying, no benefits, inconsistent workload, poor communication loop with clients are common. By employing talent full time, paying a competitive wage, with all the benefits and perks of an office job, and following local labor laws, my team really values their job.

    Here is a testamonial from one of my team, Liza, who has been with us for 6 years.

    “I find working at home very practical and convenient in terms of travel. No traffic to waste time on, this is quality time spent with the family or errands. No need for expensive clothes to wear nor uniforms to iron every day. Food is easily accessible and if you have children, no need to hire a maid just to take care of them and the household chores. Homebased jobs also make working safer and more efficient. Invaluable gave me the chance to be valuable again in the comfort of my own home. There really is no place like home.”

    And that is what makes being a Virtual Assistant with Sonic Analytics special.

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    Daniel Meyer heads Sonic Analytics, an analytics firm with offices in Manila, the San Francisco Bay Area and Ocala, FL. With over 20 years in Big Data, Dan is one of the most sought-after public speakers in Asia and offers big data coaching and analytics training seminars on both sides of the Pacific. Dan has also recently joined the Powerteam International family as a small business analytics resource speaker.

    Sonic Analytics(www.sonicanalytics.com) brings virtual staffing and big data analytics solutions like business intelligence, business dashboards and data storytelling to small and medium sized organizations looking to enhance their data-driven decision-making capabilities. We also advocate the use of analytics for civic responsibility through training, consulting and education.

    As citizens of this great democracy, we need to look at the data (analytics), plan a course of action (strategy) and share our data-driven viewpoints (presentation). This approach to a data savvy work force starts in school. So, we started an internship program to empower our youth to use Analytics, plan Strategy and Present their insights… ASP!

    When not training current and future analysts, you can find Dan championing the use of analytics to empower data-driven citizenship by volunteering his expertise with schools and non-profits dedicated to evidence-based social progress like Saint Leo University’s Women in STEAM 2020 Conference.

    I Need a Writer’s Virtual Apprentice

    The 3 Pillars of Small Business Analytics

    When I consult with small business owners, there are 3 areas where my guidance generally has the most impact. I call these areas the 3 Pillars of Small Business Analytics.

    The first pillar is a Competitive Landscape. I have found that very few small business owners really have a handle on the competition.

    A competitive landscape analysis will reveal threats and opportunities that generally are not obvious to a business owner who focuses most of his/her energy on running the business itself.

    Some of the data points you can capture and analyze include pricing, location, business size, quality, scope of business, diversity of product offering and of course revenue. You would be surprised to find how easy it is to gather all this info.

    Knowing where your products and services stack up against your competition is a key to prosperity. To achieve this understanding you need to use analytics.

    The second pillar is a Demographic Profile. I have also found that very few small business owners really understand the demographics around their business.

    A demographic profile analysis will illustrate how closely your customer base mirrors the actual population around your business. In many cases small businesses are not positioning their services correctly based on the opportunity in their market.

    Data to include would be traditional demographic markers like age, race, sex, family status, financial status, economic state, etc. There is a ridiculous amount of data on the internet that can be mined free and easy.

    Making sure your business is properly positioned to take advantage of your arket will ensure more long term success. The data is out there; you just need to know how to bring it into your analytics process.

    The third pillar is Customer Insights. With the boom in social media, most small businesses have not figured out how to capture and analyze all the information being published and shared about their business.

    Customer Insight analysis allows a business owner to stay on top of problems and identify how customers feel about their business quickly.

    We all know how quickly things can go viral and having a good tool to capture customer sentiment in social media is generally the most overlooked aspect of running a small business.

    Positive and negative reviews, trending items, number of likes, follows and shares, are all items that can be rolled into customer insights. You can combine this with surveys, focus groups and loyalty programs among other things to get a full picture of your business.

    If you are a small business owner, decision-maker or analyst then focusing on these analytics pillars will make all the difference in the world.

    And the best part, is they are all free and easy to bring into your business.

    Small Business Analytics — The field of small business analytics is just starting to blossom as companies are looking for more data-driven decision-making to prosper in the age of Big Data. Sonic Analytics is at the fore front of providing analytics training, consulting and outsourcing options to small businesses. Contact us now at info@sonicanalytics.com or connect with me directly to set up a free consultation on how to get more analytics in your small business.

    Dan Meyer heads Sonic Analytics, an analytics advocacy with offices in Manila, the San Francisco Bay Area and as of February 2019, Ocala, FL. 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.

    Sonic Analytics(www.sonicanalytics.com) brings big data analytics solutions like business intelligence, business dashboards and data storytelling to small and medium sized organizations looking to enhance their data-driven decision-making capabilities. We also advocate the use of analytics for civic responsibility through training, consulting and education.

    As citizens of this great democracy, we need to look at the data (analytics), plan a course of action (strategy) and share our data-driven viewpoints (presentation). This approach to a data savvy work force starts in school. So, we started an internship program to empower our youth to use Analytics, plan Strategy and Present their insights… ASP!

    When not training current and future analysts, you can find Dan championing the use of analytics to empower data-driven citizenship by volunteering his expertise with schools and non-profits dedicated to evidence-based social progress like Saint Leo University’s Women in Data + Science Program and the Data + Women of Tampa Meet Up Group.