Unpack the wonders of data science with digital data capture
Data, be it a small grain or in a voluminous amount is an integral part that defines the modern business domains. Excessive inbound information and its high velocity are baffling, and companies are seeking methods to utilize of these multi-directional data. But understanding the data, processing, extracting meaningful value from it, and communicating it in a beneficial way seems to be a bit trickier than what we imagine it to be.
In order to analyze the actual purpose and usability of the accumulated data, data science is introduced. This field of study examines the type of data a company receives, what it represents and how it can be transformed into valuable business knowledge. It uncovers useful intelligence and supports organizations in decision-making and devising IT strategies.
But digitization of these raw data comes with an obvious snag that is hard to ignore.
Where do the raw data come from? What is its core form and format? The majority of business data is still found in paper documents that are stored in scores of crammed locker space or in a digital mess that makes retrieving information from them a nightmare. These documents goes through a data extraction process where specific information as required for the data science project gets retrieved from the documents . Kaptiche obtains data from the available sources and extracts them avoiding unpleasant manual tasks.
Demystifying data acquisition conundrum!
For instance, the sales and marketing teams in a company are in need of mining volumes of customers’ data to identify sales patterns and thus recognize new market opportunities. But the first phase of data science – data acquisition – is intricately connected with paper documents. An organization’s historical sales reports, product performance feedback reports, won and lost deals records are paper-based and should be extracted intact to collectively form and identify meaningful patterns.
But how these paper documents are entered in the next phase of data entry? Even developed companies still resort to manual data entry which is quite cumbersome and a painful process. Manual data entry can prove to be complex, time-consuming, and expensive. If it takes enterprises days and months even to collect the necessary data, how can we expect quick access to the actionable data?
Rather than battling with tedious manual workflow, why not automate the repetitive and laborious data capture with digital data extraction?
Kaptiche data capture solution extracts all the key information from the sales documents and accomplishes this important phase of data science successfully. With quick data availability, data science assists salespeople in spotting the customers’ exact requirements and improve their conversion rates multifold.
Error-prone data extraction mars the underlying purpose!
The next common issue data scientists face is abundant errors found in the raw data. Raw data collected from paper documents tend to have human typing errors, inevitably caused by manual data entry. Even a seemingly insignificant error may lead to a chain of events that sacrifices the data quality. For example, banking institutions would mine large volumes of data for fraud detection, and federal tax authorities depend on data science to find out tax evasions. But if the quality of data entry is compromised – which is common in the case of manual data entry – the whole program of bank fraud and tax evasion detection is meaningless. That’s where Kaptiche automated data capture software comes to the aid. Kaptiche is highly accurate in its digital data extraction of the paper documents and thus eliminates errors from the extracted database.
Get your data insights straight and easy!
The third and notable application of Kaptiche data capture is that, it enables the extracted data to be electronically searchable. All the crucial information a data scientist collects amounts to nothing if he lacks immediate and easy access to it. He studies lists of channels and surveys, and if he were to make quantifiable conclusions from a set of database, he might anticipate unhindered access to the database – which is impossible if the data remains in static papers. By digitally extracting the documents, Kaptiche renders them digitally searchable and editable. No matter how large a database, data scientists and statisticians can search with few keywords and bring up the findings.
By simplifying the process of data extraction, Kaptiche automated data capture software makes the job of data science easy and thus increases the organizations’ competitive advantage in all the business paradigms.