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Data Scientist; James Maningo

James Maningo
James Maningo
Data Scientist at QuickStart

James is a stochastic tinkerer with over 8 years of experience in digital analytics. His passion lies in providing meaningful impact through data, utlizing growth hacking techniques for business and "quantified self" for personal life. His weapon of choice are linux, python, tmux+vim and good old common sense.

  1. Data Science vs Data Analytics? Which career track is right for you?

    Data Science vs Data Analytics? Which career track is right for you?

    This is the age of data! There are infinite amounts of data on the internet which users generate every day. Imagine if somehow this raw data can be processed and analyzed to extract valuable information like what the users want to see and make implementation accordingly, this could result in a state of the art digital product that addresses problems effectively. Sounds good right? All of this is possible by the use of data science and data analytics techniques.
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  2. How can I become a Data Engineer without any prior experience in the same field?

    How can I become a Data Engineer without any prior experience in the same field?

    The age of data is here! And it is here to stay! Data Engineers are equipped with a vast array for data manipulation skills, ranging from data management to machine learning. Data Engineers are literally magician who can extract valuable information out of raw data. Data engineers are responsible for the conversion of data into informative insights by using advanced analytical models. In other words, been a Data Engineer in today’s world is one of the most popular and in demand job role.
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  3. How To Decide Which Data Science Bootcamp Is Right For You

    How To Decide Which Data Science Bootcamp Is Right For You

    The world has becoming a global village, and tremendous transformations are taking place in the IT landscape. This has led to an increase in demand for skilled data scientists.  According to a Mckinsey Global institute report, demand for skilled data scientists was growing at about 12% per year as of 2016. Since then, the situation has become better since large cities in the US still battle with inadequate skilled data scientists. This further shows that there is a national shortage of about 151,717 people with data science skills in the US. Consequently, it is expected from McKinsey's report that by 2024, there is likely to be a shortage of about 250,000 data scientists in the United States. Sure, with this, you can see the obvious lucrative side of data science. Bootcamps can help you take a fast-track way to getting into the professional field of data. We’ll help you understand how to decide which data science Bootcamp will be best for you to achieve your career goals.
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  4. Why Data Scientists Are Crucial For AI Transformation

    Why Data Scientists Are Crucial For AI Transformation

    With the enormous rise in innovations in the world of data science, we can categorically say that the era of a spreadsheet is winding down very fast if not over. Activities such as Google inquiry, scanning of passport, your online shopping records are all loaded with data that can be smartly collected, intelligently analyzed, and technically interpreted to inform strategic marketing decisions that can be monetized.
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  5. The Data Scientist Job and the Future

    The Data Scientist Job and the Future

    Being a data scientist is one of the best professions a person can be in right now besides, of course, being the president of the United States.
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  6. Data Science as a Service

    Data Science as a Service

    Before you became obsessed with the data world, it is possible you had come across this strange combination of letters; DSaaS. Obviously, it would mean gibberish to a layman. However, your curiousness has pushed you towards data science, and you’re beginning to see more of this unfound word and are now asking the right questions like, “What is DSaaS?
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  7. Data Science and Big Data Analytics: Making Data-Driven Decisions

    Data Science and Big Data Analytics: Making Data-Driven Decisions

    With the need for data on the rise day in day out, there is the need to create, handle, and analyze large datasets to get prized business insights. Organizations now look for ways to gain more value from the new data they create for their customers, processes, and industries on a day-to-day basis. The questions how do data scientists, professionals, and analysts turn extensive data into actionable insights, and how do they use data efficiently? These questions and several other questions can be adequately answered by individuals who have undergone the seven weeks Data Science and Big Data Analytics: Making Data-Driven Decisions online course. Big Data Analytics and Data Science: Making Data-Driven Decisions can also be called MIT XPRO.
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  8. DATA ENGINEERS AND DATA SCIENTISTS SIMILARITIES AND TRAINING.

    Data Engineers and Data Scientists Similarities

      Data engineers and data scientists operate in an area of specialty that overlaps one another. Their skills and responsibility are on the same path, they only differ in focus. 

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