In late 1993, Jeff Bezos was a senior vice president of a prestigious NYC hedge fund. As he was researching markets for new investment opportunities, he learned a jaw-dropping fact. The Internet was growing at a staggering rate of 2,300% per year.

After thinking about this for some time, a lightbulb went off in his head. He’s going to quit his secure, high-paying job and venture into building an online bookstore. Bezos and his wife left their jobs and started Amazon from a rented car garage.  

Amazon went from selling books online to a global conglomerate with yearly revenues topping $400 billion. Conventional wisdom suggests Amazon’s secret to success is stellar customer service. According to Dave Selinger, former employee and founder of Redfin, it’s not

Bezos’s core innovation was to place data at the center of Amazon’s corporate culture. Continuous analysis of consumer and operational data allows Amazon to unearth new ways to grow the business. 

But are other businesses learning from Amazon and utilizing their own customer and operational data to gain competitive advantage and grow? Sadly, the answer is “No”. Even though we are now decades into the age of digitization, a 2020 study shows 62% of companies have not created a data-driven organization. Another study shows busessess lose $15m per year due to poor data quality. 

To make matters worse, the world is becoming increasingly more digitized. Unbelievable amounts of data are created every day. According to one report, by 2025 there’s going to be 175 zettabytes of data in the global datasphere (that’s 175 followed by 21 zeros). 

Data is so much more than an operational asset like buildings, machinery, capital, etc. Used correctly, it’s a source of new opportunities. The key to getting the most of your data is having the right data team.  

With the right data team, organizations can collect data, analyze it, and draw invaluable conclusions to drive growth. 

Here’s A List Of 7 Positions Every Data Team Needs: 

  1. API Connector/ETL Developer 

Let’s say you Google “weather in San Francisco” and find out it’s nice and warm. Curiosity kicks in and you ask yourself “How did Google know this?” Google is able to give an almost perfect answer every time using two systems: API and ETL. 

API or Application Programming Interface is a software middleman allowing two applications to talk to each other. When you ask Google a question, Google’s software sources weather information from a third party source via an API. This information is then ETL – extracted, transformed, and loaded into a database. From a database, Google pushes information onto their website for end users to see. 

  1. Data Analyst/Visualization Specialist

Our brains are not capable of interpreting large amounts of data all at once. They require visual interpretations to make sense.  

Data analysts review data to identify trends, patterns, and relationships and create graphical representations of their findings. They turn vast amounts of data into powerful visuals like dashboards, graphs, charts, and tables. 

  1. Quality Control Analyst/Developer

Quality Control Analysts or Developers apply specific methods and processes to determine whether data meets overall quality goals and criteria.They check data for errors such as missing information, duplicates, outliers, and bad data. Quality Control is essential in ensuring data accuracy and completeness. 

Credits: Unsplash
  1. Operational Process Consultant 

Operational Process Consultant advise on data integration with business processes.  Their main goal is to make sure a data team results in positive ROI. 

  1. Data Architect 

Data Architects design the blueprint a business uses for their data management framework. They define policies, procedures, models and technologies to be used in collecting, transforming, storing, and accessing data.   

  1. Business Analyst – End User Analyst

Business analysts help maximize business’s effectiveness through data-driven decisions. They use data to form insights and recommend changes. As businesses seek to increase efficiency and lower costs, business analytics has become increasingly more important. 

  1. Project Manager

Project managers organize, plan, and execute projects while working within boundaries like budget and schedule. They’re in charge of leading teams, defining organizational goals, communicating with stakeholders, and seeing a project through to completion. Project managers are responsible for the success or failure of data projects. 

3 Key Soft Skills Every Data Team Needs:

  1. Listening – every data team needs great listening skills and a clear understanding of the company’s goals and vision. Great listening skills enhance ability to understand better and improve communication. 
  2. Saying “NO” – instead of blindly following requests made by different departments, a successful data team asks more open-ended questions to get a better understanding of what is being required. Once all information is available, a successful data team can generate the right solution
  3. Focus/Drive – a successful data team also needs the right focus, drive and initiative to push things forward to solve the problem.

Data Factory Gives Your Business The FULL DATA PERSPECTIVE

Still unsure where to start? We can help!  

Data Factory is a perfect alternative for businesses not ready to build their own internal data team. We’re a full stack data team helping businesses generate insights and profit from their data. If you have any questions feel free to reach us at info@datafactory.net

Author Data Factory

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