Data Science & Data Scientist
As the world entered the era of big data, the need for its storage also grew. The main focus was on building a framework and solutions to store data. Therefore, it is very important to understand what is Data Science and how can it add value to your business.
Definition :
Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data.
In other words, Data science is a field of Big Data geared toward providing meaningful information based on large amounts of complex data.
Data science, or data-driven science, combine different fields of work in statistics and computation in order to interpret data for the purpose of decision making
Data Scientist not only does the exploratory analysis to discover insights but also uses various advanced machine learning algorithms to identify the occurrence of a particular event in the future.
Data Scientist Skills
Data scientist skills can be divided into two groups.
Technical expertise
deals directly with their knowledge of sophisticated mathematical techniques, comprehension of statistics, and technologically based skills.
Non-technical skills
involve their interpersonal skills, superior communication abilities, and strong teamwork capabilities.
Data Science Tools
Coding and programming are two very important skills that data science professionals need to possess. The following tools are used by these professionals to accomplish their tasks.
1. RapidMiner
Rapid Miner takes data scientists through the entire process of prediction modeling.
2. DataRobot
DataRobot is an automation machine designed
3. Big ML
Big ML takes the user through a series of steps it iterate different orders.
·Sources: Gathers information from a variety of locations.
· Datasets: Creates a set of data from the defined sources.
· Models: Creates predictive models.
· Predictions: Uses predictive models to create future predictions.
· Ensembles: Combines various models together.
· Evaluation: Compares models against specific validation sets.
4. Google Cloud Prediction API
This platform is for mobile applications that use the Android platform...
5. Narrative Science
Narrative Science is a data science tool that creates targeted reports from the statistics it is given.
6. ML Base
The goal of this large-scale data science tool is to help provide secure solutions to a large subset of common problems.
7. Automatic Statistician
It takes in data from a variety of sources and creates detailed reports using natural language processing.
Benefits of data science
As data and technology became more available and companies can profit more by informing their decisions by it, there is a growing need to bridge that gap. For this, you need a different kind of employee who combines strong analytical skills with strong business skills. And this is exactly the role of data scientist.
Definition :
Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data.
In other words, Data science is a field of Big Data geared toward providing meaningful information based on large amounts of complex data.
Data science, or data-driven science, combine different fields of work in statistics and computation in order to interpret data for the purpose of decision making
Data Scientist not only does the exploratory analysis to discover insights but also uses various advanced machine learning algorithms to identify the occurrence of a particular event in the future.
Data Scientist Skills
Data scientist skills can be divided into two groups.
Technical expertise
deals directly with their knowledge of sophisticated mathematical techniques, comprehension of statistics, and technologically based skills.
Non-technical skills
involve their interpersonal skills, superior communication abilities, and strong teamwork capabilities.
Data Science Tools
Coding and programming are two very important skills that data science professionals need to possess. The following tools are used by these professionals to accomplish their tasks.
1. RapidMiner
Rapid Miner takes data scientists through the entire process of prediction modeling.
2. DataRobot
DataRobot is an automation machine designed
3. Big ML
Big ML takes the user through a series of steps it iterate different orders.
·Sources: Gathers information from a variety of locations.
· Datasets: Creates a set of data from the defined sources.
· Models: Creates predictive models.
· Predictions: Uses predictive models to create future predictions.
· Ensembles: Combines various models together.
· Evaluation: Compares models against specific validation sets.
4. Google Cloud Prediction API
This platform is for mobile applications that use the Android platform...
5. Narrative Science
Narrative Science is a data science tool that creates targeted reports from the statistics it is given.
6. ML Base
The goal of this large-scale data science tool is to help provide secure solutions to a large subset of common problems.
7. Automatic Statistician
It takes in data from a variety of sources and creates detailed reports using natural language processing.
Benefits of data science
- Innovation
- Exploration
- Challenge the status with radical new solutions
- improve existing processes and products
- Identify the drivers of certain undesirable situations
As data and technology became more available and companies can profit more by informing their decisions by it, there is a growing need to bridge that gap. For this, you need a different kind of employee who combines strong analytical skills with strong business skills. And this is exactly the role of data scientist.
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