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Why Every Enterprise Needs Data and Analytics

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Understanding the concepts of data and analytics is only a stepping stone to the benefits received from applying them correctly. So how can you leverage these technologies and methodologies to help your organization? In this section of the article, we discuss why enterprises that intend to stay relevant in the coming decade need data and analytics.

Understanding Big Data

Big Data refers to large datasets that come into networks in the form of unstructured and random data from a variety of sources such as websites, social media, and various other sources. These data are random and don’t align with any data models or structures. They have to be sorted into a coherent whole before you can understand their implications and analyze them to reveal trends and patterns. Big data may include data in the form of text, videos, pictures, audio, and various other types of files.

The entire field of data analytics — including data engineering, artificial intelligence, machine learning, etc. — is used to make sense of the data. Data analysis is necessary to sort them out into recognizable and identifiable compartments or categories. Following that, data analysis deploys tools to analyze the data and offer easily-understandable insights in the form of charts and graphs so you can make intelligent decisions. Without data analysis, all of the data harvested by your sources will be useless.

 

Identifying Data Sources

As previously mentioned, data in modern enterprises come in from a variety of sources. You may receive data from social media, websites, e-commerce platforms, customer relationship management portals, spreadsheets, backups, and various others. However, all of these data is unstructured, so you can’t identify where they’re coming from and what the patterns are.

Data analysis allows you to identify where all of the data and information is coming from. Once you’ve identified the sources, you can gauge the patterns and trends to facilitate business decisions and improvements. The decisions you make based on the available information may range from being extremely simple to extremely complex.

A simple and basic example of data analysis using data source information is the timing and scheduling of invoice cycles for maximum efficiency. More complex use of this data analysis may be predicting market trends and the popularity of your offerings based on factors like weather, market demands, geography, customer information, etc

 

Using Analytic Tools

To understand what the data tells you about your organization, you need to access and correctly leverage your analytic tools. Modern data analysis uses a wide range of user-friendly analytic tools that help you make sense of big data. The data collected is automatically compiled and generated into various forms of visuals. The visual depends on the data you are studying and the information revealed. These visual aids and cues can help you understand data better than any other source.

 

Organizational Planning

The primary goal of data analysis is to help steer an enterprise or company in a forward direction — to help it grow by learning from the past. As mentioned in the previous points, data analysis can help with operational efficiency, which ensures that business continues functioning effectively. Information provided by data analysis can help you figure out which are fundamental weaknesses of your organization so you can rectify those inefficiencies. This also helps with risk management solutions to chart a company’s growth and progress.
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The following are some of the primary benefits of organizational planning using data analysis:
• Better understand company expenditures to see where the logistical department is being efficient or inefficient
• Predict customer demands based on current purchase trends and market analysis. This helps the company adjust its supply for the future
• Guge and track employee efficiency more accurately. This allows the company to determine which employees are adding value, how to incentivize them correctly, and how to reward employees that are performing well
• Better manage financial risks by understanding operational capabilities
• Finally, organizational planning through data analysis also allows an enterprise to determine when it’s worth taking financial risks to balance risks against rewards

 

Marketing

Data analysis of social media trends and customer engagement has drastically disrupted the marketing industry. Traditional forms of marketing have become common as all major enterprises focus on customer insight and social media analysis.

Social media is currently the strongest determinant of what the public wants or needs. However, social media is also a completely random, unpredictable, and unorganized mess in terms of data analysis. That’s why social media demands can only be accurately tracked using advanced data analytics tools.

Data analysis can help with marketing in the following ways:
• Social listening to see how often people talk about individual businesses
• Gauging which users are most influential in the social community so that the company can target them with marketing efforts
• Understanding how their target audience talks to connect with them
• Studying social metrics like click-through rates, bounce rates, etc., to determine how well certain marketing efforts are working — and then modifying them accordingly


Conclusion

Data and analytics is the future of all enterprises — it’s simply too valuable and has too much potential to be ignored. Businesses generate massive amounts of data daily, and it’s impossible to sift through them and make any sense of them without data analysis insights. Without data analytics, you can’t reach ultimate organizational efficiency, customer engagement, or marketing.

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