Without the right mindset, strategy, technology, and resources, the way you deal with big data could be hindering your business intelligence (BI), analytics, and innovation goals. The outcome? A stagnant, disintegrated business that fails to meet customer demands and falls behind its competitors. But what you should do to evade this ill fate? Well, you need to avoid three of the biggest integration challenges.
Here are a few major data integration challenges that your organization must avoid in order to speed up growth.
As per a KPMG survey, 77% of respondents (out of a group of 400 chief executives) agreed that they had faced internal data quality concerns in their companies.
It’s no secret that this has proven to be one of the most important challenges in the data-driven organization, with a multitude of organizations dealing with this problem on a daily basis. Poor data quality due to “unclean data” can severely harm your business. It can lead to bad analysis and even worse, bad decisions. This not only damages your reputation but also causes revenue loss.
Solution: Data integration solutions need to incorporate more data quality functions to assure that integrated data has the highest value and most impact possible. For this, businesses need to make use of modern integration technologies that allow organizations extract insights from data keeping the quality intact.
Data security is another aspect that can’t be ignored. Organizations need to ensure that all data stored are secured and confidential before and post-integration. Poor data security standards in an enterprise can lead to data leakage and data breaches, decreasing data integrity substantially. Companies, therefore, can experience revenue losses and low levels of productivity.
Solution: To deal with data security problems, organizations need to employ a data integration solution that offers an end-to-end encrypted environment for all data that is transferred and exchanged across the business ecosystem. Such a solution only allows authorized and authenticated users to access data, thereby eliminating the risks of breaches or theft.
As per research, data analysts invest nearly one-third of their time on data preparation. With the increase in data volume and speed, organizations need to look for time, resources, and appropriate manpower to handle data preparation challenges. This, as a result, slows companies’ growth and rate of innovation.
Solution: To combat these challenges, a lot of companies are investing in a new set of technologies such as self-service integration. Organizations can use these tools to explore, manipulate, and merge new data sources – all without the assistance of IT staff.