Algorithms Could Pave Way for Automated Data Entry
Algorithms are all around us – from Internet search engines such as Google to our mobile phones and beyond. In its most basic form, an algorithm is simply a set of rules or a process to be observed in problem-solving or calculations. This particularly involves processes and transactions on a computer or mobile devices.
Algorithms have already fueled a great deal of the current economic and technological revolution. But what about future algorithms still to be developed? In this article, DataEntryOutsourced focuses on the potential of automated data entry – facilitated by algorithms and predictive analytics.
Why Is Automated Data Entry Needed for the Future?
Simply stated, human data entry might not be a sustainable business model for the future. In an increasingly automated world, common errors due to data entry need to be eliminated in the “next wave” of technological progress. For example, data duplication and inaccurate data can lead to bigger and bigger problems down the line. One data entry error in statistics can cause a significant t-test to show up as non-significant or turn a moderate correlation into zero. To minimize data entry errors, machine learning algorithms and predictive modeling algorithms are likely to play significant roles as we move forward.
Algorithms for Predictive Modeling
Algorithms have already played a productive role in helping all of us to cope with a “Big Data” world. One of the “priceless” advantages of algorithms is the ability to take an almost unlimited number of factors into account within a very short span of time. For example, Google’s search engine algorithm can help you find answers to virtually any search query in less time than it takes to sip your coffee or tea (or perhaps something stronger).
Predictive modeling takes traditional algorithms one step further by using trends and forecasting probabilities in conjunction with predictive modeling algorithms. In many cases, businesses want to predict future consumer behavior, and predictive modeling is already used widely to help companies of all sizes do a much better job of effectively “seeing the future before it happens” – by using algorithms that help in making accurate forecasts of how prospective buyers will probably behave in the future.
Machine Learning for Automated Data Entry
Machine learning can be compared to the data mining process since both involve looking for patterns while searching through data. But while data mining focuses on data extraction for human analysis, machine learning programs and algorithms use the discovered data to improve the program as more processes and calculations are made. For example, some mobile phones will “suggest” certain words and phrases for texting based on your earlier uses – by learning how you have used certain word combinations in the past and then “predicting” what you might want to say next.
A similar approach seems possible for data entry – particularly if machine-learning software is used in a data entry program.
Combining Human Intuition with Automated Data Entry
Could data entry become totally automated in the future? While it is possible, an ongoing blend of real (humans) and artificial (machines) intelligence seems to make the most business sense for contemporary data entry tasks.
DataEntryOutsourced has literally “seen it all” during the past decade in the data entry field – what works, what doesn’t work and the role of outsourcing data entry jobs as an effective solution in reducing data entry errors for DEO clients. We have always been committed to providing the “best of both worlds” to DEO customers by helping them save money, reduce turnaround times and improve quality in our data entry work.
Highly skilled humans are still very much a critical part of the process at DataEntryOutsourced – but we do blend state-of-the-art technology and human intuition as part of our successful strategy to reduce data entry errors while offering our clients cost-effective and timely services.
What are your experiences with both data entry and algorithms? We’d love to hear from you, so please leave comments below and then share your thoughts by using the social media buttons.
– DataEntryOutsourced
