Data aggregation is a common term these days in the tech industry, but what does it really mean? In this article we clear up the confusion around ‘data lakes’ and ‘data clouds’ that are being created to improve data-driven decision making.
Data aggregation is the process of gathering information from a variety of sources and presenting it in a simplified format The data is gathered with the intent of providing a summary for analysis which would then provide unique insights which would have been overlooked or impossible to discern. Simply put data aggregation is merely combining data from various departments in an organization to reveal insights that may have not been available before. To illustrate this case let us continue with the fictional company which was outlined in the article on RPA (Robotic Process Automation) which can be found here.
As Jane is working hard to process orders, we see that she needs to update three separate systems (Order fulfillment, Accounting, CRM). Once her work is complete the following will most likely occur:
Jamie in the warehouse will periodically update the order fulfillment system until it is complete.
Tom in accounting will process the payment and close the order once it has been fulfilled.
Jim will update the CRM (Customer Relationship Management) database for follow up regarding product satisfaction.
Now let us take a look at how each department could benefit from the information currently trapped in separate systems.
Jim can provide real-time updates to the customer regarding early (or late) delivery. This enables the organization to get ahead of any potentially negative social media feedback by offering coupons, incentives, etc.
Tom can provide more accurate financial forecasting based on the ebb and flow of inventory in the warehouse.
Jamie can use customer order information to minimize inventory which improves organizational cashflow. Additionally, if the widget is produced inhouse customer feedback can inform future improvements and offerings.
While this is a simplified example, we see that as long as our data is trapped in disparate systems these insights are not available. Data aggregation allows for a unified dataset containing all relevant information for better decision-making.
Data aggregation is a common term these days in the tech industry, but what does it really mean? In this article we clear up the confusion around ‘data lakes’ and ‘data clouds’ that are being created to improve data-driven decision making.
Data aggregation is the process of gathering information from a variety of sources and presenting it in a simplified format The data is gathered with the intent of providing a summary for analysis which would then provide unique insights which would have been overlooked or impossible to discern. Simply put data aggregation is merely combining data from various departments in an organization to reveal insights that may have not been available before. To illustrate this case let us continue with the fictional company which was outlined in the article on RPA (Robotic Process Automation) which can be found here.
As Jane is working hard to process orders, we see that she needs to update three separate systems (Order fulfillment, Accounting, CRM). Once her work is complete the following will most likely occur:
Jamie in the warehouse will periodically update the order fulfillment system until it is complete.
Tom in accounting will process the payment and close the order once it has been fulfilled.
Jim will update the CRM (Customer Relationship Management) database for follow up regarding product satisfaction.
Now let us take a look at how each department could benefit from the information currently trapped in separate systems.
Jim can provide real-time updates to the customer regarding early (or late) delivery. This enables the organization to get ahead of any potentially negative social media feedback by offering coupons, incentives, etc.
Tom can provide more accurate financial forecasting based on the ebb and flow of inventory in the warehouse.
Jamie can use customer order information to minimize inventory which improves organizational cashflow. Additionally, if the widget is produced inhouse customer feedback can inform future improvements and offerings.
While this is a simplified example, we see that as long as our data is trapped in disparate systems these insights are not available. Data aggregation allows for a unified dataset containing all relevant information for better decision-making.
Financial and Investing
Since many investors leverage the news for near real-time information financial firms use data aggregation to gather headlines and articles for predictive analytics. Trends, perspectives and events that could affect financial forecasts of companies and products are compiled and used for recommendations and investments.
Retail
One of the most common uses for data aggregation in this industry is competitive price monitoring. As ecommerce giants like Amazon have grown brick and mortars such as Target need to know what they are up against. Information must be pulled continuously from competitor product offerings to inform pricing and promotions.
Travelocity
As mentioned earlier the travel industry is extremely complex with narrow profit margins. Travelocity aggregates and maintains a database of competitor pricing, research, travel trends, and customer satisfaction. This information is updated in near real-time and then reflected in all their customer contact mediums (website, phone, etc.).
Netflix
While the majority of the entertainment industry uses pilot testing to determine content popularity and make purchasing decisions, Netflix leverages the vast amounts of data accumulated on organic viewing behavior. While a customer is consuming content every start, stop, pause, etc. is recorded and aggregated for further analysis. In Sebastian Wernicke’s excellent TEDX talk which can be found here he illustrates how both Netflix and Amazon use data to guide their investments.
Office Depot
In order to stay competitive Office Depot aggregates data from its online and traditional outlets. By maintaining a unified set of information regarding customer buying habits and competitor pricing rapid decisions can be made regarding pricing, promotions, purchasing and more.
Travel
Gaining market intelligence may be considered the difference between survival and extinction in this industry. Travel agencies need not only understand the pricing of their competitors but also the ever-fluctuating costs of flights, hotels, cruises, and any other fares related to their product offerings. As you can imagine this information is extremely time sensitive making manual aggregation in a timely manner impossible.
In addition to the use cases above, the following real-world examples highlight competitive advantages many organizations have gained using data aggregation.
Financial and Investing
Since many investors leverage the news for near real-time information financial firms use data aggregation to gather headlines and articles for predictive analytics. Trends, perspectives and events that could affect financial forecasts of companies and products are compiled and used for recommendations and investments.
Retail
One of the most common uses for data aggregation in this industry is competitive price monitoring. As ecommerce giants like Amazon have grown brick and mortars such as Target need to know what they are up against. Information must be pulled continuously from competitor product offerings to inform pricing and promotions.
Travelocity
As mentioned earlier the travel industry is extremely complex with narrow profit margins. Travelocity aggregates and maintains a database of competitor pricing, research, travel trends, and customer satisfaction. This information is updated in near real-time and then reflected in all their customer contact mediums (website, phone, etc.).
Netflix
While the majority of the entertainment industry uses pilot testing to determine content popularity and make purchasing decisions, Netflix leverages the vast amounts of data accumulated on organic viewing behavior. While a customer is consuming content every start, stop, pause, etc. is recorded and aggregated for further analysis. In Sebastian Wernicke’s excellent TEDX talk which can be found here he illustrates how both Netflix and Amazon use data to guide their investments.
Office Depot
In order to stay competitive Office Depot aggregates data from its online and traditional outlets. By maintaining a unified set of information regarding customer buying habits and competitor pricing rapid decisions can be made regarding pricing, promotions, purchasing and more.
Travel
Gaining market intelligence may be considered the difference between survival and extinction in this industry. Travel agencies need not only understand the pricing of their competitors but also the ever-fluctuating costs of flights, hotels, cruises, and any other fares related to their product offerings. As you can imagine this information is extremely time sensitive making manual aggregation in a timely manner impossible.
In addition to the use cases above, the following real-world examples highlight competitive advantages many organizations have gained using data aggregation.
Regardless of sector data aggregation can benefit any organization seeking to gain competitive advantages. Additionally, through the use of technology is possible for much less than previously possible. With that said, aggregation is only one piece of a larger journey. Simply pooling information in one place will not reveal the insights necessary to make better decisions. To fully realize the investment a combination of business process management and workflow automation should be considered to ensure once data is aggregated it can be maintained, updated, and analyzed without the need for manual intervention. Odesso has over twenty years of combined industry experience and helped many organizations achieve their goals. To learn more review our case studies here.
428 E Thunderbird Rd, #716, Phoenix, AZ 85022, USA
| (323) 807 6590 | © 2024 Odesso, Inc. All Rights Reserved
