Will A.I. Take My Job… and other Big Data Questions I’ve Been Asked Lately

The more I go around speaking and talking about big data, analytics and getting companies more A.I. ready, the more I find myself answering some common questions about these topics.

Here are a few I get asked on a regular basis.

1.) Are data analysts in demand?

2.) What does a data visualization specialist do?

3.) To learn AI, should I know data science?

4.) What will be the impact of the role of artificial intelligence in business?

5.) What is data mining used for in a business?

Data Jobs — By 2030, it’s projected we will be over 80 million workers short when you look at jobs available and workers with the mostly tech based skills needed to fill them. Let that sink in a moment. It’s not just that data analysts are in demand, the demand for them will boom in the next decade.

Data Visualization Specialists — A DVS is responsible for taking data and turning it into insight. Using visuals like pie chart, line graphs, maps, and infographics a DVS converts what most people struggle with making sense of, numbers, into much easier to understand visuals. Most people learn visually, but most data visualization don’t employ simple strategies geared towards educating, empowering or influencing their audience through the appropriate use of data visualizations. A good DVS can employ data storytelling techniques in powerful ways, using dashboards and storyboards that are much more impactful then simple management report using Excel’s built in graphsand charts.

A.I. and Data Science — To design, create, maintain and/or evolve A.I., you will need to know many things that are common to most data scientists like predictive model building and statistical analysis. However, teaching machines to learn generally requires skills with certain applications (like tensorflow) that many not be used in most data science jobs. Same with building customer behavior influencer models. That said when you look at apps like Waze, you see the work of both data scientists and A.I. experts, so in the end they can arguably be considered one.

Business Uses of A.I. — The most common use of A.I. in business is in a process automation of collecting, storing, analyzing and/or sharing data. Building models to influence customer behavior (when you see things pop up in your news feed, that you end up clicking on) is another common use of A.I. The tech titans and unicorns all are heavily invested in A.I.. Apps like Uber would not work effectively if they didn’t massively employ A.I. You are also seeing more and more chatbots, replace customer service staff. That’s just a few examples of how a business can get started with using A.I.

Data Mining — Data mining is pretty board term, but at its simplest it is using technology to locate, collect, extract, store and organize data in volumes we could not do with just human effort. Data mining includes scrapping data off web sites, doing massive SEO keyword searches, extracting a few data point from mountains of big data, the refining of raw data into actionable information and on and on. Data mining is an area, where A.I. can play a big role in automating processes that a lot companies have set up using very manual workflows.

Daniel 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 offers big data coaching and analytics training seminarson 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 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.