14 new roles in Big Data
The amount of data is growing every day in huge jerks. Every day, 2.3 trillion gigabytes of data are poured into the network. By 2017, the amount of data is expected to grow by 800%. The more data, the higher the demand for specialists in their processing.
Data science is developing so dynamically that each specialist has his own narrow area of responsibility. Martin Jones, CEO and co-founder of Cambriano Energy, proposes to highlight 14 key roles in working with big data.
This is a specialist who works with alternative data sources. It forms the market and demand, supports the data market and constantly replenishes it with new values. Traders look for potentially valuable data, research new flows and market them.
Data Trader also seeks and explores tools for data processing for its customers. He evaluates and predicts trends and conducts transactions for the purchase of data that may become popular in the future.
Data Hound is the trader’s right hand. After the trader made a forecast, Data Hound is taken for the work. His task is to find the best, cheapest and most reliable source of big data and calculate the contacts of the owners and suppliers of this very data.
Only Data Hound can infect everyone with enthusiasm and inspire you to work with new data. He must be sweet and patient and possess the tremendous power of persuasion. And only he can dispel all doubts when working with the new data portal.
This specialist designs and supports the entire infrastructure. It provides data delivery, ensures that the data goes through all stages: preparation, cleaning, analysis and presentation.
Data Plumber must make sure that the data has gone through all stages of processing and has passed from the provider to the data consumer.
His typical areas of responsibility are:
Data Butcher works in tandem with Data Shef. He selects and prepares the necessary parts of the supplied data, which he then passes to the boss for the mining date, predictive analysis and visualization. Data Butcher separates interesting data from unnecessary. The output is high-quality, structured data, which is then analyzed. We can say that Data Butcher is a special case of a data architect.
Without a doubt - this is the most difficult and stressful role. The miner is always busy with logical and physical research. It identifies and retrieves the most inaccessible data with the highest information value. Most likely, these data are very deeply buried and his task is to take risks and extract them to the surface. Such data have a very high coefficient of utility and will be used for a long time. That is why the work of the date miner will always be in demand in the world of big data.
Data Canary controls the quality of the data extracted by the data miner and helps him to evaluate them sensibly.
When there is more data than the resource can process or when “toxic” data is embedded in the business process, then Data Pharmacist comes into play. He must have remarkable mathematical abilities to identify problems and find a way to fix them.
Accuracy and pedantry are his main qualities. Even minor errors can lead to misuse and interpretation of data. Data Pharmacists typically work in multitasking mode and need to make decisions quickly.
He must also have excellent communication skills, as he interacts daily with a large number of annoyed people, advises them, answers questions and reassures.
Data Pharmacist is a very patient, very attentive extrovert mathematician.
Also, this role can be called: Data Janitor or Data Custodian. Data Caretaker takes care of data centers, clouds and data warehouses. It ensures the security and cleanliness of storage and data.
To become such a specialist you need to have practical skills in Python programming, data scrambling and DIY modeling. In this role, work experience is always preferable to higher education.
The main task of Data Cleaner is to identify and dispose of toxic and viral values that can distort the nature of the data. They make sure that the data is clean, representative and suitable for processing.
Data Chef organizes and coordinates the work of all departments. Ideally, the Chef has knowledge in analytics, has solid experience in statistics and a solid understanding of data architecture. And also in his resume is written a wide range of other skills that can be listed forever.
Data Chef, together with Data Trader and Data Butcher, finds and selects raw raw data. And based on this data, Data Chef draws up a plan for their processing and selects an analysis method, even if the data changes dynamically over time.
Data Taster is a person who tries (tests) data or information before sending it to the consumer. There is always a risk that the output may be erroneous or misleading.
For example, Data Taster checks and confirms that the data is current and the models used are valid.
It can also be involved in the preparation and presentation of data. Such a specialist should be very scrupulous, because incorrect output data affect his reputation.
In a simple way, Data Server presents data and accepts orders. He can also advise his customers on the optimal data selection based on the available data and the preferences of other customers.
Narrator, merry fellow and philosopher. The main task of this person is to help the client correctly interpret the results, present and explain everything in a simple and accessible language. Data Whisperer is the premier empathy in the world of big data.
Usually this role is played by CFO or the person following it. He must be aware of all the nomenclature values and all actions within the organization. He manages everything, copes with various business tasks, breaks walls and achieves all the best for his team.
Data science is developing so dynamically that each specialist has his own narrow area of responsibility. Martin Jones, CEO and co-founder of Cambriano Energy, proposes to highlight 14 key roles in working with big data.
Roles and responsibilities
Data trader
This is a specialist who works with alternative data sources. It forms the market and demand, supports the data market and constantly replenishes it with new values. Traders look for potentially valuable data, research new flows and market them.
Data Trader also seeks and explores tools for data processing for its customers. He evaluates and predicts trends and conducts transactions for the purchase of data that may become popular in the future.
Data hound
Data Hound is the trader’s right hand. After the trader made a forecast, Data Hound is taken for the work. His task is to find the best, cheapest and most reliable source of big data and calculate the contacts of the owners and suppliers of this very data.
Only Data Hound can infect everyone with enthusiasm and inspire you to work with new data. He must be sweet and patient and possess the tremendous power of persuasion. And only he can dispel all doubts when working with the new data portal.
Data plumber
This specialist designs and supports the entire infrastructure. It provides data delivery, ensures that the data goes through all stages: preparation, cleaning, analysis and presentation.
Data Plumber must make sure that the data has gone through all stages of processing and has passed from the provider to the data consumer.
His typical areas of responsibility are:
- Knowledge of the specifications and capabilities of information repositories and knowledge bases.
- Detection of errors in the operation of these systems and diagnosis of the causes.
- Location and labeling of wires, adapters, ports and channels for receiving and sending data. As well as support for the correct operation of data centers.
Data butcher
Data Butcher works in tandem with Data Shef. He selects and prepares the necessary parts of the supplied data, which he then passes to the boss for the mining date, predictive analysis and visualization. Data Butcher separates interesting data from unnecessary. The output is high-quality, structured data, which is then analyzed. We can say that Data Butcher is a special case of a data architect.
Data miner
Without a doubt - this is the most difficult and stressful role. The miner is always busy with logical and physical research. It identifies and retrieves the most inaccessible data with the highest information value. Most likely, these data are very deeply buried and his task is to take risks and extract them to the surface. Such data have a very high coefficient of utility and will be used for a long time. That is why the work of the date miner will always be in demand in the world of big data.
Data canary
Data Canary controls the quality of the data extracted by the data miner and helps him to evaluate them sensibly.
Data pharmacist
When there is more data than the resource can process or when “toxic” data is embedded in the business process, then Data Pharmacist comes into play. He must have remarkable mathematical abilities to identify problems and find a way to fix them.
Accuracy and pedantry are his main qualities. Even minor errors can lead to misuse and interpretation of data. Data Pharmacists typically work in multitasking mode and need to make decisions quickly.
He must also have excellent communication skills, as he interacts daily with a large number of annoyed people, advises them, answers questions and reassures.
Data Pharmacist is a very patient, very attentive extrovert mathematician.
Data caretaker
Also, this role can be called: Data Janitor or Data Custodian. Data Caretaker takes care of data centers, clouds and data warehouses. It ensures the security and cleanliness of storage and data.
To become such a specialist you need to have practical skills in Python programming, data scrambling and DIY modeling. In this role, work experience is always preferable to higher education.
Data cleaner
The main task of Data Cleaner is to identify and dispose of toxic and viral values that can distort the nature of the data. They make sure that the data is clean, representative and suitable for processing.
Data chef
Data Chef organizes and coordinates the work of all departments. Ideally, the Chef has knowledge in analytics, has solid experience in statistics and a solid understanding of data architecture. And also in his resume is written a wide range of other skills that can be listed forever.
Data Chef, together with Data Trader and Data Butcher, finds and selects raw raw data. And based on this data, Data Chef draws up a plan for their processing and selects an analysis method, even if the data changes dynamically over time.
Data taster
Data Taster is a person who tries (tests) data or information before sending it to the consumer. There is always a risk that the output may be erroneous or misleading.
For example, Data Taster checks and confirms that the data is current and the models used are valid.
It can also be involved in the preparation and presentation of data. Such a specialist should be very scrupulous, because incorrect output data affect his reputation.
Data server
In a simple way, Data Server presents data and accepts orders. He can also advise his customers on the optimal data selection based on the available data and the preferences of other customers.
Data whisperer
Narrator, merry fellow and philosopher. The main task of this person is to help the client correctly interpret the results, present and explain everything in a simple and accessible language. Data Whisperer is the premier empathy in the world of big data.
Data czar
Usually this role is played by CFO or the person following it. He must be aware of all the nomenclature values and all actions within the organization. He manages everything, copes with various business tasks, breaks walls and achieves all the best for his team.
Abstract
- By 2017, the amount of data is expected to grow by 800%.
- Martin Jones, CEO and co-founder of Cambriano Energy, proposes to highlight 14 key roles in working with big data.