The amount of data that is being generated every day is increasing at an enormous rate. Almost ninety percent of the data that exists today was generated in the last two years. Can you imagine?
Now, to equip and take advantage of big data faster than the competition, exceptional data professionals are high in demand.
What is Big Data?
Big data refers to immense groups of data that are analyzed computationally to reveal patterns, trends, and combinations. There are a lot of different origins of big data. Transactions, log data, social media, and Company emails are the largest sources of data housed within organizations.
External data sources can comprise of everything from social media, photos and videos and even audio files. As technology and the internet transformed the workforce, it resulted in the production of enormous amounts of data which can be utilized by an organization to make better business solutions.
How is Big Data used?
The main purpose of using Big Data is to discover how the gathered data can be used for the benefit of the organization, to solve problems and also discover problems in order to make better business decisions.
Any firm can use historical data and mathematical models to maximize their returns. Companies can use their purchase data to identify customer preferences, fluctuations in demand and behaviour metrics to ensure they are delivering the right products to their clients.
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How to Prepare for a Career in Big Data.
Big data is only as good as the information that can be collected from it. So professionals with proper technical understanding and reasoning are in high demand. According to the Bureau of labour and statics, the field is expected to grow 27.9 percent from 2016-2026, making its rate of growth faster than any other occupation. The career paths in this field vary widely from industry to business needs.
A data analyst at a web development company could have a whole different role from a data analyst at a healthcare company. Database executives have different functions, training, and backgrounds than different engineers.
Let’s take a look at the requirements needed to become a data analyst.
There does not exist a degree or a grad course in big data, there are skills and educational backgrounds that can help define your career path.
One needs to obtain a bachelor’s degree in an analytical or mathematics- oriented field such as statistics, computer science, information management, are some of the many fields which tend to be an excellent foundation for a big data career.
You will also need to build and develop relevant skills through professional IT training courses and certifications which will help you to enter the big data field.
Big Data Skill Sets
Before you want to work with Big Data, you will want to spend some time developing your portfolio of data skills. Here are some technologies which you will need to grab a hold on before you enter the workforce.
Hadoop: This is an open source software framework for running applications and storing data provides massive storage and processing power to handle large quantities of data.
SQL Database and Querying skills: the majority of organizations rely on SQL database to organize and store their data, so managing the SQL data warehouse and also extracting the information needed using advanced SQL queries is a must for anyone who wants to enter this field.
Data mining: The process of checking large databases top generate new information, this is one of the most critical skills required for data professionals.
Microsoft: Microsoft offers a vast variety of data science tools and services which can be used to process and analyze big data.
Data professionals draw the line between technical data analysis and business development. To communicate the data effectively to non-technical teams and fellow employees of the organization should not be a problem.
Important soft skills for big data professionals are:
- Problem-solving skills
- Communicating across your organization
- IT service management
- Leadership quality
- Project management
6 Big Data Career Paths
Big data career paths encircle both data management and data analysis roles.
Database developers and administrators develop and maintain the IT mainframe which supports the Big Data. Other roles include the use of Big Data to generate actionable insights which the organizations can use in decision making, strategic planning, and business development.
1. Database Administrator
Average Salary Range: $98,000-$140,000
Database administrators are responsible for the purity, performance and the security of a database. Planning databases and monitoring them to ensure data security is the main duties which one needs to perform under this category of Big data.
2. Database Developer
Average Salary Range: $70,000-$100,000
Database developer’s deals with the design of the database. They may eliminate inefficient coding to improve database performance and upgrade the database with zero errors.
3. Data Analyst
Average Salary Range: $77,000-$118,000
After the database has been designed and managed, it’s time to analyze it. Data analysts collect, analyze and perform statistical data analysis, working with large volumes of data to turn it into business insights which the team members can use.
4. Data Scientist
Average Salary Range: $90,000-$110,000
Data scientists are heavily involved in the statistical analysis to create new algorithms to analyze and utilize data. They use all the data in identifying high-level business trends and insights.
5. Big Data Engineer
Average Salary Range: $95,000-$150,000
Data Engineers are focused on the infrastructure, but they aren’t responsible for maintaining it. They design and manage how data is housed and build scalable, high- performance mainframe which delivers cohesive information from raw data sources.
6. Data Modeler
Average Salary Range: $111,000-$160,000
Data modelers turn business requirements into conceptual and physical data models. Basically, A data model is a representation of the business and information needs in an enterprise.
Big Data Training with New Horizons
Big Data has exploded over the last decade and shows no sign of slowing down. One should look out for opportunities in this field as it is not dying soon because it has just begun.