But thou, O Daniel, shut up the words, and seal the book, even to the time of the end: many shall run to and fro, and knowledge shall be increased.
Daniel 12:4
Big Data
That’s a prophecy from the Bible that is quite an understatement today. As of the date of this writing, the index web contains 2.25 billion pages. The International Data Corporation (IDC) estimates that the global datasphere will grow to 175 zettabytes by 2025 (1 ZB equals 1 trillion GB). And that grows exponentially with social media, smartphones, and the Internet of Things (IoT) feeding it more data.
Big Data , by definition, is huge data in size. So big it crashes your Excel spreadsheet. Big data describes a collection of data that is huge and yet growing exponentially with time. It redefines how we run government, industry, business, and science.
American biologist, naturalist, entomologist, and writer E. O. Wilson said, “We are drowning in information while starving for wisdom. The world henceforth will be run by synthesizers, people able to put together the right information at the right time, think critically about it, and make important choices wisely.”
Big Future
Data science makes the above possible. It is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data and apply knowledge from data across a broad range of application domains. It includes data mining, machine learning, computational statistics, and analytics.
This gives rise to the “mind workers,” jobs that did not exist ten or even five years ago.
Data Analyst
They are the gatekeepers for an organization’s data. A data analyst collects and stores data on sales numbers, market research, logistics, linguistics, or other behaviors to help people, businesses, and organizations make better decisions. Although you don’t need a computer science degree, you need to know some mathematics and statistics, programming languages like SQL and Python, and data visualization tools like R and Power BI. Salary ranges from $98,682 to $112,593 per year.
Data Scientist
While Data Analyst answers questions, Data scientists determine the questions their team should be asking and figure out how to answer them using data. They often develop predictive models for theorizing and forecasting, data modeling processes to create algorithms and predictive models, and perform custom analyses. Data Scientist skills include machine learning, statistical modeling, and artificial intelligence. The salary range typically falls between $117,238 and $145,020 per year.
Data Engineer
He is responsible for extracting, compiling, and analyzing large amounts of data from different sources. With over 2.5 quintillion bytes of data created daily, all organizations need employees who can make sense of huge volumes of data. A data engineer must have strong analytical skills to draw insights from large amounts of data, plus Hadoop and Kafka. Salary ranges from $ 77,000 to $115 000.
Data Architect
They are IT professionals tasked with defining policies, procedures, models, and technologies which will collect organize, store, and retrieve information for the organization. They define how the data will be stored, consumed, integrated, and managed by different data entities and IT systems. The skills include the basics of columnar and NoSQL databases, data visualization, unstructured data, and predictive analytics, as well as data mining, visualization, and Machine Learning skills. The average salary rate is $118,868.
Even with the ever-changing job market, these jobs above are future-proof and will be in demand even for many years.
