Making Data Better – Resolving Inefficiencies in Data Preparation

Limited by the technology and manners in which we store data, finding the right data to use is an immense task in and of itself; and the chaotic nature of data makes us susceptible to problems with data management.

Due to these constraints, analysts waste precious time finding data critical to their business and verifying the validity and sources. Only then can the data be prepared for mass viewing and usage. According to a survey conducted by Anaconda, data scientists spend 45% of their time preparing data, which involves cleaning data and resolving redundancies too, both of which carry significant overhead costs.

The task of sorting out discrepancies and readying data for perusal is inefficient to say the least, with the average business reporting losses to the tune of $15 million per year solely due to such inefficiencies. Moreover, data preparation has been proven to have a negative impact on job satisfaction levels.

In order to ensure a data analyst in your organization is provided with the right data, it needs to have a credible source, valid and verified, non-problematic metadata, and most importantly consistent data quality of a high level. It becomes hard to trust your data when you constantly come across discrepancies that get in the way of real data science tasks.

In turn these lead to issues with data discovery, as enterprises have trouble locating and pinpointing the data they need in order to make the right business decisions, and lack of quality data doesn’t help the cause. Of course, the data lineage can be traced, and one can carry out a set of procedures to be able to trust the data at hand.

While this is one of the best ways to tackle the numerous issues one can have with source and format discrepancies, to do this every time you collect or locate data adds to the list of inefficiencies throughout the actual process of using that data.

Steps to take towards increasing the efficiency of your data

The best way to make data usable in shorter periods of time, with minimal redundancies and discrepancies, is to organize your data. It might sound easy enough, but as we mentioned above, organizing the data you think you require is a trial-and-error process that ultimately results in loss of time and money, therefore building an archive of all the data you could possibly want and have is a mammoth task, especially when you want to also be able to have some command over said data.

There are plenty of different avenues of action you can take towards organizing and arranging your data, including data profiling and cataloging. Nevertheless, data prepping has been known to take up a crucial 80% of a data scientist’s time, and the lack of good quality data that can be trusted by every member of your team acts as a hindrance towards enterprise data management, especially when it comes to managing employees and sharing one particular vision for the company. 

Enterprise data management is a well-known term that encompasses the process of ensuring you have the best possible data in order to maximize workflow and streamline communication within your organization, resulting in the improvised ability to make key business decisions, both individually and collaboratively.

Benefits of Enterprise Data Management with Global IDs

By organizing, classifying, categorizing, and creating a data catalog, your data can be seen systematically and according to relevance. You can ascertain a certain command over the data available to you and your organization, making it easier for you to locate and trust your data, while controlling parameters such as metrics and KPI’s to be relevant and precise.

Having data of such quality and consistency results in more transparency within members of the organization when it comes to the data being used, which can in turn allow you to make smarter and more unanimous business decisions. Having data that can be trusted by the whole enterprise only promotes collaborative approaches to loading and defining data, as well as sustaining information flow in the most rapidly changing work environments.

The ultimate aim of this is to empower your organization with the ability to view data from a unified perspective with respect to data assets; promoting communication within the enterprise, and providing your organization with a boost in productivity, as you spend significantly less time finding, loading and prepping data for your perusal, while saving money on the overhead costs of data cleansing.

Making Data Better with Global IDs

At Global IDs, we deliver an integration platform to deliver trusted data in order to enable businesses to achieve growth in the manner intended. Better data leads to optimized processes and reporting, delivering significant cost reduction in resources and improving time to market.

At Global IDs, we strive to promote a higher level of data literacy, and a large part of that involves using our solutions to obtain the most relevant data and information from the scores of legacy data available to an organization, nurturing collective and constructive advancement in the world of data analytics and metadata management.