In this age of “Big Data”, the bigger problem than the data being BIG is the poor quality of the data. The digital universe seems to have an increasingly endless amount of data. In this digital world with the infinite amount of accumulated data, the businesses are fetching a mixed buffet of good and bad data. However, this buffet will be healthier if you clean and scrub it before your business consumes it expecting it to create some value. Consider the data you have collected as raw vegetables which require a neat preparation for converting it to a dish that is meaningful. Just as preparing food with care and hygiene is inevitable for the sound health of a person, similarly, data hygiene is instrumental for the success of your business strategy.
How is Data Scrubbing Different From Data Cleansing?
Let us first understand the definition of data scrubbing. Wikipedia defines data scrubbing as – “Data scrubbing is an error correction technique that uses a background task to periodically inspect main memory or storage for errors, then correct detected errors using redundant data in the form of different checksums or copies of data.”
In simple words, data scrubbing can be envisioned as the early steps of repairing and fixing the data issues and making it ready to be transferred to the data warehouse.
Data Scrubbing and Data Cleansing are usually confused as same processes and these terms are often used inter changeably. But let us understand the fine line between them.
Data Cleansing is the simple process of removing inefficient data from the whole data, while data scrubbing involves repairing, merging, decoding, filtering, and translating the data through specialized processes. It is the process required after cleaning the data and before storing the data for its further use. Data scrubbing services also include timely check and filtration of inconsistencies from the data present in your business warehouse.
Data Scrubbing and Business Process Optimization
In today’s big data environment, automation plays a leading role in varied business processes. Also, the huge amount of data acts a downfall for the maintenance of data quality. Data mistakes are an undesired side effect of the absence of industry-wide data standards and aging of data algorithms.
Businesses are using data as a protagonist for their various business strategies because it helps in generating bounteous value for a business. The benefit that clean data can lend to a business, the same amount of decline or even more is what bad data can bring to your business.
From 17% in 2015, big data adoption has reached up to 53% in 2017. This stats show how the use of data is marking clear growth for businesses. Since businesses know the significance of using data for growth, timely CRM data cleansing and data scrubbing services remained the top-notch priority of majority businesses as it could optimize your business strategies.
Cost Implications of Inadequate Data
According to an estimate, the US economy spends around $3.1 trillion a year in eliminating the dirty data.It is not surprising as bad data could misguide business processes. You can now imagine how big would be your problem if your business data expires to a major extent. It could make a staggering impact. Average businesses are likely to lose 15 to 25% of the net income due to inadequate data.
Data Scrubbing services matter as it could leave your business in a distressing condition. With high-end algorithms and customized tools, we are here to help. You can connect to make a difference.
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