The data science revolution has come to stay, and businesses are scrambling to keep up with the changes it entails. That is to say, companies all over the world are building big data strategies by encouraging their employees to develop expertise and implement data science technologies.

Check out these stats:

  • 59% of businesses around the world are already adopting big data analytics;
  • 79% of executives agree that their business will perish if they don’t embrace big data;
  • 49% of entrepreneurs agree that big data analytics helps them cut expenses, and 44% confirm they use data science for innovation.

Considering the increasing interest in data science, businesses simply cannot stay behind. And, although data science as a field is still developing, there are 4 reasons we encourage you to start building for the future of your business using data science.

Companies using analytics


Table of contents

1. Generate unique insights
2. Increase competitiveness and performance with Machine Learning
3. Use Data Science to optimize and automate business processes
4. Forecast the future of your business with patterns
Conclusion


1. Generate unique insights

Data science eliminates a lot of the guesswork when it comes to creating marketing campaigns, deciding what content to publish, or developing new products. Data analytics enables you to have a 360-degree perspective of your customers, thus allowing you to better understand them and address their needs.

Establishing which metrics provide valuable information for your particular industry will help you leverage that information to give you an advantage in the market. You can use the insights you gain from data analytics to make better decisions which will lead to better outcomes.

Data is information, generally sets of numbers or text. Insights are the knowledge gained through analyzing data, generating conclusions from the data that can benefit your business.

There are also lots of questions in regards to the differences between data scientists, data analysts and data engineers are because all of them take aspects of each others.

Data insights might include:

  • Noticing that certain weekends of the year are in higher demand for your product or service, allowing you to raise prices during these times;
  • Monitoring your company’s online advertising performance data to determine which campaigns, audiences, and ads are effective and which are not.

2.Increase competitiveness and performance with Machine Learning

Machine learning is used across industries, including healthcare, automotive, financial services, cloud service providers, and much more. With machine learning, you can get improved performance in several areas, including:

  • Image classification and object detection
  • Fraud detection
  • Facial recognition
  • Image tagging
  • Big data pattern detection
  • Network intrusion detection
  • Targeted ads
  • Computer server monitoring

Machine learning allows your business to anticipate and preemptively satisfy customer needs, increase the efficiency of inventory systems, and reduce the number of human errors produced by manually processing data.

In practical terms, advanced business intelligence and the application of Machine Learning means increased KPIs (both for your business and your employees), better ROI, and improved revenue. By implementing ML solutions to your business, you’ll have access to:

  • Higher-quality insights about business processes and customers
  • Better solutions to conventional problems and radical solutions to arising issues
  • Continuous improvement of existing processes
  • Prediction of potential problems
  • Discovery of new areas of business growth by analyzing untapped sources of unstructured data

Fact: According to the MIT Technology Review Custom survey, 60% of respondents reinforce their companies with ML in one form or another. By implementing ML, businesses hope to gain 3 key benefits: new insights through data (50%), a competitive advantage (46%), and faster data analysis (45%).

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3.Use Data Science to optimize and automate business processes

Data science provides businesses with a plethora of options for optimizing business operations. Take, for example, the manufacturing industry. Data analytics and IIoT (Industrial Internet of Things) are becoming increasingly popular among manufacturing facilities. Data is collected and analyzed using sensor technologies and real-time tracking systems, which manufacturers can later use to:

  • Eliminate bottlenecks in the manufacturing process
  • Increase the efficiency of the assets
  • Track product quality and defects
  • Do product testing
  • Data science helps manufacturers to reduce production issues that can impact the quality of the product or the logistics within the production facility as well as the shipment process.

Data science may also be used to power HR apps, which can help with recruiting and employee management. AI-enabled HR tools can help employers automate a variety of employee management tasks, including:

  • Simplify employee onboarding
  • Manage employee workload
  • Run performance reviews and assign employee rewards
  • Collect employee training data

AI-enabled HR apps also help with recruitment, helping HR managers screen and source job applications as well as analyze the conversations with job candidates, and pick the best talent.

4.Forecast the future of your business with patterns

By using current and historical data you can accurately predict future trends and forecasts. With the constant change of our everyday lives, Data Science can bring better insights into the future than humans, by spotting patterns we might not always see.

Forecasting allows you to make data-driven business decisions and establish data-driven strategies. Financial and operational decisions are based both on current market conditions and predictions of the future. Past data is compiled and examined to uncover patterns, which are then used to forecast future trends and changes. Forecasting enables your business to be proactive rather than reactive.

Three ways forecasting can help your organization excel:

  • Helps set goals and plan;
  • Helps budget;
  • Helps anticipate change within the market.

Conclusion

Building the data science competency of a company is an ongoing job. As this field develops, professionals will find more and more opportunities to enter the emerging world of data analytics and business intelligence. Becoming more data-savvy is a great chance to increase your portfolio and remain competitive in the future.

If data integration is something new in your strategy, then staff extension may just be what you’re looking for. And we know just the place to find a solution for all your data needs!

Imaginary Cloud provides award-winning AI and Data Science services and has taken businesses to the next level for more than a decade.

Are you looking to develop a solid data strategy and improve business results?

Get in touch with us here!