In the quest for a competitive advantage, many are turning to predictive analytics.
Predictive analytics can forecast future outcomes using historical data combined with statistical modeling, data-mining techniques and machine learning, explains technology corporation IBM. Companies, governments and several industries use predictive analytics to find patterns in data to identify risks and opportunities.
Although predictive analytics has been around for several years, it is growing in popularity because technology has become faster, easier and less expensive to use.
Analytics Applications
Predictive analytics has widespread applications. Major uses, according to Investopedia, include weather forecasting, creating video games, translating voice to text for mobile phone messaging, customer service and investment portfolio development.
Additionally, analytics software developer SAS Institute describes the importance of predictive analytics in detecting fraud and cybercrime prevention, optimizing marketing campaigns, improving business operations and reducing risk.
There are challenges for predictive analysis, however. For example, some data might come from irrelevant sources that provide more noise than actionable insights. Inaccurate data can also skew results.
Despite the possible challenges, many organizations are using predictive analytics to achieve optimal business outcomes.
The Future of Business
Financial services, health care, manufacturing and retail are among the industries using predictive data analytics to improve performance. Costs, competition and consumers are driving businesses to be more forward-looking. Predictive analytics has become a priority for many businesses seeking to make well-informed and fact-based decisions about future scenarios.
Predictive analytics has the power to help businesses stay relevant in an ever-evolving world. Investment in the tools and people to perform data analysis is viewed as worthwhile and logical.
Qualities Needed to Succeed in Data Analytics
Organizations today require expertise in data analytics. There are many technical skills data analysts can possess that will attract employers, and there are also soft skills that are important in the field. Among these soft skills are:
- Communication, needed by data analysts to share their findings in a way that is easy to understand.
- Problem-solving when issues occur. Data analysts must be able to troubleshoot the problem so they can continue to work efficiently.
- Researching to be able to find the information that can help them interpret raw data.
- Attention to detail, which helps to notice small details that contribute to the larger picture.
You Can Meet Today’s Demand for Data Analysis
Carlow University offers a bachelor’s degree in Data Analytics that can give you the skills needed for the high-demand field of data analysis. In this degree program, you can build critical thinking, analytical, and business skills, supplemented with courses in mathematics, statistics, and computer programming. Coursework includes database management and applications such as SQL, R Programming and Python.
Choose the data analytics degree program and gain the foundation needed to help organizations improve, grow, and stay competitive.