5 Top Reasons For Automated Data Integration?

5 Top Reasons For Automated Data Integration?

It has been a long since the marketing team has known the importance of data. Studies prove that the more a business is data integrated, the better the performance. This holds only if you have the required resources at hand.

Marketing analysts perform operations starting from data collection, analysis, research, reporting, and visualization. If the initial processes are automated, more focus can be laid on advanced stages. Herein, we will understand the top reasons why automated data integration is a significant need for any marketing analyst:

1. Saves time and effort

Usually, the daily tasks are conducted manually using spreadsheets. Data collection, cleaning, and combining are challenging tasks if done manually. Automated data integration comes to aid as manual process saves 80% of the time.?

2.?Generate value?

Usually, organizations hire a marketing analyst having extensive knowledge in analytics. However, their tasks end up in data cleaning and integration. The scope of operations of the marketing analysts is even much more. Spending so much time on data integration could give less space to analyze it. However, this could happen only if the mundane and redundant tasks are automated.

Also, the results proved that organizations could make more financial savings if the marketing analysts were bound to perform their creative task of data analysis.

3.?Effective decisions

Decisions are the natural outcome of the analysis. If the study is slow, the decisions are also slow. So, seeking proper channels to accelerate the workflow is an effective option. Adopting them much early in the project life cycle could cause huge savings.?

Significant insights are lost if you take days to copy the data into the spreadsheets. This reveals that the more time you take to perform data analysis, the vast expenditure and competitors have a wide space to beat you.

4.?Data accuracy

Most analysts complain about the quality of the data they receive. Inaccurate data results in incorrect insights. So, this is the central issue that needs to be dealt with primarily. The first step would be to eliminate the manual procedures, which are more likely to be prone to human errors. Studies suggest that marketing analysts dealing with manual methods finds four times more complexity in attaining accuracy.?

5.?Satisfaction :

Data cleaning and integration are usually tasks to generate marketing reports. Spending too much time doing it is an inefficient process. Analysts aspire to spend less time on it and focus on the essentials. Predictive modeling is a practical step, as suggested by most data analysts, even though the necessary prerequisite is not in place.?

The skilled marketing analysts should perform much beyond everyday operations. Employees' unhappiness and dissatisfaction are the natural outcomes If they are limited to conducting such activities.

Conclusion

Modern-day marketing analytics have to perform automated data integration . Their capabilities surpass the traditional means of cleaning and combining the data. So, the marketing teams should do their best to generate value for their analysts. So, leverage the marketing technology to streamline data integration with automation.

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