Businesses of all kinds have seized the advantages made possible through using big data to better understand their position in the marketplace. There are clear advantages for organizations in gathering and analyzing vast bodies of quantitative information. With the right tools, people and processes in place, big data yields deep insights into customer behaviors and provides robust predictive power.
To achieve the full potential of big data, a business must have a team of professionals with the necessary expertise. Graduates from data analytics master’s programs are prepared to take on the leadership roles that make data work for an organization. There are many different positions available.
Each organization has its own particular sources and needs for quantitative findings. When a business needs customized tools to aggregate and interpret data, developers are tasked with creating the necessary programs and applications. The individuals in these roles may take on a wide variety of specialties:
- Hadoop developers, experienced in working with the Java-based open-source framework for processing big data, are in constant demand to establish new systems.
- Extract, Transform and Load developers create the tools for bringing together and storing relevant data in the form that fits the organization’s needs.
- Visualization-tool developers offer the means to arrange information in ways where it can be more readily analyzed.
- Predictive-analytics developers concentrate on modeling business scenarios and using historical data to project future performance.
As big data has become an increasingly essential part of how companies do business, there is a need for an expert to ensure the staff in various departments have the information they require. A database manager is responsible for making big data accessible throughout the organization. They supervise the collection and management of information in a central database system.
Database managers provide workers with the knowledge to take advantage of that information. This commonly involves creating documentation and providing training sessions. The manager makes sure data is being used properly for the daily tasks of business and contributing to the overall mission of the organization.
These experts find ways to improve business processes and solve problems. Examining rich sources of data, they discover meaningful patterns and offer direction through statistical and analytical methods. Data scientists contribute to the organization’s use of big data by performing tasks like:
- Using programs and algorithms to gather quantitative information.
- Detecting and scrubbing anomalies that would interfere with analysis.
- Structuring analytical findings so they have business applications.
- Communicating meaningful insights to business and IT leaders.
- Presenting findings with clear visualizations.
A data scientist finds links between the huge amounts of information available to organizations and the specific challenges they are facing. Data-driven businesses rely heavily on the strategic guidance data scientists provide, using the analytical findings to formulate actionable plans for achieving their goals.
Data architects establish the procedures and models for how the organization gathers, stores and manages information. The layers of processing they set up work to provide various departments with the specific pieces of data they need. An architect finds the best ways to synthesize information from multiple sources, discovering how to keep processes running faster and predicting any conflicts that might lie ahead.
A data architect works closely with decision-makers and IT specialists to continue meeting the needs of the company. These professionals need to translate the particular requirements of departments into rules for processing data. As those requirements change, the architects optimize the architecture so data systems pull from new sources and continue working efficiently.
The big-data engineer puts the processing models designed by the architect into action. These individuals use their background in software engineering and database technology to develop and test those solutions. They implement projects to collect, analyze, warehouse and transform data.
Engineers solve problems for the organization, often focusing on complex but rewarding concepts like data mining or machine learning. A powerful, agile arrangement for processing information can make the difference in a big-data strategy’s success. Consequently, engineers often work closely with data scientists to ensure they have the right platform to fulfill the needs of the business.
The education for a career in analytics
Building a career in big data takes an advanced education in the relevant technology and processes. With an online master’s degree in data analytics from Villanova University, you’ll gain the knowledge and skills to turn quantitative information into powerful business intelligence. Visit the program page to learn more about preparing yourself to seek work as an analytics professional.