Five ways to improve data analysis

Data teams around the world constantly collect, ingest, classify, transform, and analyze data as part of their daily business practice. Going through large amounts of data can be overwhelming, especially with so many data-driven tools and resources available on the market. Data analytics is a rapidly changing space, and staying on top of data is important to meet customer needs, identify market trends, and react to customer desires quickly. It’s a challenge for many companies to figure out exactly what are the best ways to improve this process with so many options at their disposal. Don’t worry, because we’ve done the research so you don’t have to and have found five ways to improve your data analysis below.

business intelligence tools

Business Intelligence (BI) tools are one of the easiest ways to improve data analysis for any business. Business intelligence is the process of turning raw data into meaningful information, which teams can use to make strategic decisions. BI tools discover insights and turn them into easy-to-use data, such as tables, charts, reports, and dashboards. You don’t have to be highly versed in the technicalities of data to get the most out of BI. In fact, BI allows both business leaders and data analysts to tailor BI to their level of knowledge, enabling them to make smarter decisions. Additionally, BI enables you to identify trends, cultivate insights, and take actionable action from your data. Popular and trusted tools that businesses most commonly use include Tableau, Datapine, Sisense, and more.

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data hygiene

Keeping your data clean, fresh, and up-to-date is probably one of the most essential ways to improve your data analysis. According to AccuData, most companies lose up to 12% of revenue due to the presence of dirty data. Dirty data consists of outdated, duplicate, incomplete, and incorrect data. Data teams work hard to keep your data error-free so you can successfully connect with your customers, improve lead tracking, and personalize campaigns and ads the right way. Finding ways to create standardization within your databases and cultivating dirty data prevention practices are critical to a company’s success. Some of the top data cleansing tools include Trifacta Wrangler, Tibco Clarity, Data Ladder, and more.

data enrichment

Data enrichment is a great way for any company to learn how to improve their data analysis. Data enrichment is the process of taking unique data points and connecting them to external data sources. This process helps businesses obtain additional information about leads, website visitors, and specific demographics. You can get additional information about people with valuable data points such as email addresses, phone numbers, and IP addresses. Data enrichment can help you get a complete picture of customers, make more informed decisions, and strengthen fraud prevention. Some of the most trusted data enrichment tools include Clearbit, MaxMind, ZoomInfo, and more.

Reverse ETL

The Extract, Transform, and Reverse Load (ETL) process is one of the best ways to improve data analysis across the board. Reverse ETL is the process of moving data from a data warehouse to an operating system of record. Reverse ETL is most commonly used to achieve data activation, which is known as the final step in the modern data stack. Data activation gives you real-time insights into your customers, giving you the power to make better decisions, improve the customer experience, and increase productivity within your organization. You can also use reverse ETL to sync your data with operational tools, marketing applications, and customer relationship management (CRM) platforms. Some popular ETL tools include Hightouch, Hevo Activate, Census, and more.

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Customer segmentation

Leveraging customer segmentation is another valuable way to improve data analytics for your business. Customer segmentation helps business leaders better understand their customer groups. This gives them the power to understand customers based on geographic, demographic, and behavioral segmentation. There are so many ways you can use this data to target your audiences based on things like hobbies, age, habits, income, education, location, etc. You can use this to create more personalized experiences, increase revenue, and keep customers coming. back for more. Data teams can also track people throughout the customer journey and gain insights to improve the experience for others. Popular customer segmentation tools include Amplitude, Baremetrics, Userpilot, and more.

Conclusion

Data analytics is essential for any business looking to gain a competitive advantage and continue to meet the needs of its customers. Investing in data analytics is a worthwhile endeavor, but it can be frustrating with so many tools available to data teams. Simple ways you can improve your data analysis include looking into BI tools, improving your data hygiene practices, and investing in data enrichment. Two other trusted ways to improve data analytics include reverse ETL for data activation and customer segmentation. Implementing these five ways highlighted above will help you improve your data analysis and help your customers stay happy.

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Categories: Technology
Source: vtt.edu.vn

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