Ensuring data quality is of paramount importance in today’s data-driven business world because poor quality can render all kinds of data completely useless. Moreover, this data is unreliable and lead to faulty business strategies if analyzed. Data quality is the key to making trustworthy business decisions.
Companies lacking correct data-quality framework are likely to encounter a crisis situation. According to certain reports, big companies are incurring losses of around $9 million/year due to poor data quality. Back in 2013, US Postal Service spent around $1.5 billion in processing mails that were undelivered due to bad data quality.
While the sources of poor quality data can be many, including data entry, data processing and stale data, data in motion is the most vulnerable. The moment data enters the systems of an organization it starts to move. There’s a lot of uncertainty about how to monitor moving data, and the existing processes are fragmented and ad-hoc. Data environments are becoming more and more complex, and the volume, variety and speed of big data can be quite overwhelming.
Here, we have listed some essential steps to ensure that your data is consistently of good quality.
Thus, achieving high-quality data requires an all-inclusive platform that continuously monitors data and flags and stops bad data before they can harm business processes. Hadoop is the popular choice for data quality management across the entire enterprise.
If you are looking for big data Hadoop certification in Gurgaon, visit Dexlab Analytics. We are offering flat 10% discount on our big data Hadoop training courses in Gurgaon. Interested students all over India must visit our website for more details. Our professional guidance will prove highly beneficial for all those wanting to build a career in the field of big data analytics.
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