How to Improve Data Extraction Performance

improve data extraction performance

Most businesses today rely on some form of data to provide goods and services, manage how their business is run, or identify new growth opportunities. When data is accessible, accurate, and has context, it can be transformed into valuable intelligence. This knowledge has become critical for companies to operate with greater precision, performance, and profitability. It also provides organizations with the opportunity to deliver a superior level of customer satisfaction. Organizations looking to maximize the value of their data must first master their data extraction performance.

What Is Data Extraction?

Data extraction is simply the process of collecting data from a variety of sources. The objective is to standardize this process so it can be automated with the highest level of accuracy, resulting in a collection of structured data. This data can then be used to perform queries or analytics calculations and provide valuable business intelligence. Each time you act to prepare and retrieve data – and then move that data to another location – you are performing data extraction.

There are three different levels of data extraction –  bulk extraction, incremental extraction, and update notification. Each serves a different need, so your best choice depends upon the objective you are looking to achieve.

  • Bulk Extraction – as it sounds, this is the process of capturing or extracting an entire dataset from its source; given this will often involve large data transfers, it can take longer and sometimes require more resources to complete. In situations where new information is presented, this is likely the only option to consider.
  • Incremental Extraction – this is a process where data is extracted only when a change is performed at the source; think of this as a way to ensure a dataset remains current as new information becomes available or as things change. A benefit of this approach is that less time is spent performing the extraction process, as it eliminates the need to re-extract the full dataset every time there’s a change or update.
  • Update Notification – as the least intrusive form of data extraction, this is a strategy whereby notification is sent each time data changes in the core dataset; it is then up to the database administrator or user to decide if this new data is worthy of being extracted and added.

Why Perform Data Extraction?

Companies operating today – such as those in the Real Estate industry – rely heavily on the use of digital systems, processes, and software applications to operate with the greatest efficiency and accuracy. A digital transformation has brought on this change – and has significantly impacted nearly every industry as a result. The global pandemic has only amplified this need for digitalization, and the resulting impact on commerce, consumer expectations, and how businesses operate.

Digital capabilities are now a prerequisite to compete in the long term. As McKinsey explains, over time, digitalization transforms industries creating disruption along the way. A critical capability for long-term survival is to embrace digital technologies. This means it is necessary to consolidate data from disparate sources and aggregate it to a single location. This is the only way to unlock the value of all this data is by transforming raw data into business intelligence. Other benefits of adhering to this strategy are to:

  • Reduce data entry errors
  • Increase employee efficiency and productivity, and
  • Drive forward automation and process improvement strategies

How Can You Improve Performance?

The best way to improve the performance of a strategic process is to first take a close examination of each component of the process. In this case, that means taking a look at the origin of where the data comes from in your business. What is the source, how well can it be relied upon, and what can be done to ensure its accuracy is at the highest possible level?

The next step is to look at whether the data that is being extracted and added into your company’s “data ecosystem” is structured or unstructured. If it is structured, then it is already in a format like a spreadsheet or data table, so is ready for extraction. Alternatively, if it is unstructured, such as information on a social media feed, handwritten, an email, or another more complex source, then an additional step is necessary to clean up this data before performing an extraction.

This article may be of interest and provide greater insights on how to best add structure to improve the performance of data extraction of unstructured data, How to Overcome Data Extraction Challenges for Smart Business Performance.

Once your data has been adequately cleaned and grouped as structured data, the next step is to review how quickly and effectively the process is to move this data to your central repository or warehouse. Be sure to examine the resources involved, time invested, and the accuracy percentage achieved of completing the data extraction process. No matter how well designed or how high the performance is of your existing system and process, it will never be 100 percent perfect. There will always be exceptions that must be manually cleaned or adjusted.

If the accuracy percentage performance of your data extraction process is less than 90 percent, you have room for improvement. Consider speaking with a data extraction specialist that can provide suggestions, insights, or a service that can enable you to improve your performance.

Axis Technical