In the last few years, digitization has swept industries off their feet. More and more organizations are establishing their presence online and reaching out to customers like never before. This digitization pushes businesses and industries not only on the Internet but also on many channels.
For an ordinary business, this would mean taking their retail processes to their very own website. However, it will not be limited to just that. Businesses are also encouraged to sell their goods and services in a market where they reach an audience that already establishes. Apart from this, businesses will also be eager to reach out to their customers on platforms like social media. Facebook, Instagram among others are, turning into prime selling channels.
Businesses are eager to take advantage of these platforms since they already have a well-established customer base. It directly helps enhance sales, improve branding along with other factors, even for an ordinary enterprise.
However, the more platforms one establishes their presence over, the more sources of data generated. Online presence already comes with an abundance of data by the way customers interact with your presence. For example, customers might purchase your products, reach out to your customer support along with just interacting with your website. All these help generate data because one way or the other, everything can be tracked over the Internet.
More Sources of Data
The point is data has become an asset in the modern world. We are generating an abundant amount of data from different sources. And this is becoming a turning point for enterprises. Based on the understanding and analysis of this data, organizations can move a step closer to understanding the customer.
One of the simplest ways that data can put to use is through demand forecasting. For example, customers interact more closely with certain ways of your business, which means they will make purchases at multiple touchpoints you provide through digital and non-digital media. When you compile all this data and perform data analytics on top of it, you will be able to understand how customer demands shape.
You can answer questions like:
- Why are my customers purchasing a single product?
- When is the demand for a particular product the highest?
- What is the best season to sell a particular kind of product?
- Which products sell well during which seasons?
- How do I prepare my inventory/service for an order surge?
All these and more questions are answered with the help of analysis of data, This directly boosts the business of an enterprise and helps them take strategic steps that are backed by data. On one hand, this practice results in direct customer profits, while on the other helps create customer satisfaction on an entirely different level.
The Age of ETL
As enticing as it sounds, the task of bringing together or compiling the data from multiple sources is a cumbersome task. While small businesses might be able to do it manually because of their limited presence and other factors such as small business size, the manual task is close to impossible as the business grows.
Generally speaking, as well, the burden for a majority of tasks is passed onto automation as an enterprise begins to grow. That means they no longer have to dedicate resources to viewing data from multiple sources and integrate them onto a single platform so that everything makes sense. Instead, this job is given to an ETL.
For those who know about it, ETL is becoming excessively popular because it is helping enterprises capture the right amount of data from different platforms. It is helping them see the bigger picture of things and analyze data that is complete rather than broken. Such a unified process also ensures that enterprises can curate customer experiences from a holistic point of view and identify whether customers like one touchpoint more than the other.
Moreover, ETL stands for Extract, Transform, and Load. It is typically a process where different types of data are collected and refined. Upon these actions, they are delivered to a data warehouse for safekeeping. Going forward, why ETL data integration will become a preferred choice of tool is because they enable migration of data between a different variety of sources, destinations and analysis tools.
For this reason, ETL ensures business intelligence and contributes towards a broader data management strategies. The data extraction, data transformation, and data load steps form the pillars of the ETL software and help businesses gove a tough competition in the market.
The 2020 outlook for ETL suggests that the top players of the ETL software industry include names like:
Additionally, ETL can be classified based on two parameters in 2020 and beyond. These are either by their type or their application. When it comes to type, ETL can be dismantled into cloud-based and web-based software. Similarly, if you take a look at the applications, ETL can be looked upon for large enterprises as well as small and medium enterprises.
While ETLs are being used extensively across industries, the dominant regions where they are centered right now are the Middle East and Africa, North America, South America, Europe, and the Asia Pacific.
The goal of ETL is to deliver business intelligence. It allows companies to combine legacy data with current data to get historical content. In the long run, it improves the efficiency and productivity of an enterprise.