The role of the Data Janitor is often overlooked and instead passed to the Data Scientist; distracting them from the bigger picture and analytical duties. This can be detrimental to the company and could end up costing millions.
Data is now among the most valuable assets for most companies, often overtaking the more traditional tangible assets. The largest companies are now those who own data, process data as a core activity and treat data as an asset to drive their business. To achieve a data driven organisation, it is essential that data is managed properly.
Welcome to the Data Revolution
Only 15 years ago the world’s largest, by market capitalisation, companies produced engines, raw materials and medicines or provided financial services. Nowadays, most of the largest companies produce data. Out of the 10 biggest companies only two – Apple and Johnson & Johnson – produce tangible products. In terms of income, the banks are still in the lead.
Investors say that being capable of managing data became more and more important in all scales.
How good is your data?
Data affects all processes of companies from planning to delivering their products or services. Businesses cannot thrive on poor data quality. Data acquired from a wide variety of sources must be suitable for the purpose it was collected for. Accurate, consistent and complete enough, in a reasonable format with the required granularity, reaching their points of usage in a reasonable time. Using inappropriate, badly structured data may lead to poor decision making, missed business opportunities and thus inhibit organisations from achieving their goals. The problems will grow exponentially without processes that address data quality.
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1-10-100 4 trillion
According to Gartner and IBM, US companies lose $4 trillion per year due to bad data quality. The 1-10-100 rule states that it would cost $1 to verify a piece of data as it’s entered, it would cost the companies 10 times more to fix it later if it proves to be faulty and 100 times more to leave the faulty record as it is. These enormous numbers, even if they may seem to be exaggerated, show that the need for improving data quality represents great opportunities to amend the bottom line of the companies as well as for consultancies to help their clients manage their data issues with their special knowledge.
Data Scientists and Digital Janitors
Digital janitors have a special role in preparing the data for the business users, analysts or data scientists. They maintain the database, cleanse the data, make sure that backups and archives are performed in due time but they are not involved in activities like analysis.
Data scientists, on the other hand, deal with the big picture, manage large data sets, perform complex and innovative analysis, and provide tools that help drive the business.
Poor data quality would lead to data scientists devoting their time and skills to daily routine tasks instead of innovation, turning data into valuable insights and contributing to the success of the company.
What can you do?
Businesses are in perpetual change, they grow, adapt to the ever changing environment and their customer needs. The amount of data they produce and use grows at an even greater pace, often exponentially. Managing this data is crucial and this includes not only gathering and storing the pieces of data. It also means utilising the above mentioned human resources effectively within their roles as well as build a sustainable, scalable and effective physical and logical data structure. Companies have to build firm data paths from the points of entry across various systems, this means data remains available, up to date, accurate, consistent and complete, and a high level of data quality is achieved.
How can Dufrain help you to achieve these goals?
To find out more about data preparation and profiling, ETL, and other Data Management approaches or to discuss your data challenges with one of our experts, simply get in touch to start the conversation.
Sources:
- Your-data-scientist-digital-janitor-robert-baer
- Visual capitalist
- Forbes.com
- Bad-data-costs-the-us-3-trillion-per-year
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