Data Transformation: How it Transforms the Enterprise Landscape

Data has emerged as one of the most valuable assets for enterprises in the 21^st century. It is no wonder now why companies owning the largest amounts of data are also among the biggest enterprises in the world today. Be it Google, Amazon, Microsoft or social media giants like Meta (previously Facebook), the entire business of these companies is data-dependent. Such has been the charm of data in today's era that even old businesses or economies, that thrived on other assets in the past, are now rapidly putting data at the centre of all their plans.

However, like all other assets, enterprises need to harness data properly to reap the long-term benefits. Data can help in making smarter decisions that can put an enterprise ahead of its competitors. But not all data is relevant. In its raw form, data can be compared with the mineral ore freshly procured from a mine. To get something useful out of the ore, one needs to work on it, process it and refine it. The same rule applies to data as well. Enterprises need to refine or transform data to make some business sense out of it.

These days most of the consumer data is stored on enterprise or public cloud systems. Companies need this data to run analytics and drive insights into consumer behaviour and demand. These insights help enterprises in creating strategies for every stage of the marketing funnel. However, the data available on these platforms is often in multiple formats and structures and is not compatible with all systems. To drive insights and generate reports from heterogeneous data formats and structures, enterprises depend on data transformation techniques that help solve compatibility issues and make the available data more consistent. In simple terms, data transformation is the process of changing the available data format into a usable format for the target system or application.

Some commonly used data transformation processes include aggregation, sorting and data cleaning. These processes help convert the raw data into the required format for the destination system. The data transformation activities also include transforming the data based on certain rules and joining different fields to get an easily understandable consolidated view. Data transformation makes it easy to grasp and use data for both computers and humans alike. In a world, which is undergoing digital transformation at an unimagined pace, data transformation can help transform the fortunes of enterprises.

The following points further explain how this is possible:

Improves data quality

Quality of data is important for all enterprises. The data that doesn't make sense is of no use to the business. Data transformation not just improves the quality of data but also reduces the number of mistakes such as missing values, making the data more usable for advanced business analytics.

Makes data management easy

 Data transformation makes it easy to manage and organise the data in the desired format. Better data management reduces errors and helps build trust in the data, helping enterprises in making better business decisions.  Enterprises these days are sitting on mountains of data. A report has predicted that by 2025, the total data stored globally in the cloud itself will reach 100 zettabytes, while total global data storage may exceed 200 zettabytes. (1 zettabyte is equal to 1 trillion GB). With so much data in the cloud and other storage, companies that can manage their data efficiently are likely to grow faster in the coming years.

Improves enterprise efficiency

In the past, organisations used to be run by certain thumb rules and gut-instinct decisions of top managers. The availability of data and transformation tools has now made it possible for organisations to make fool-proof smart decisions to improve efficiency in a quick time. Many organisations these days fail to adequately tap into the immense potential of data. However, in current times, a failure to properly use data may even lead to the shutdown of firms. Enterprises these days need to do better, as being 'good enough' is not enough. To become efficient, they need to leverage data and make the most of transformation techniques.

Enables timely action

Data transformation enables organisations to take timely data-backed actions. If done correctly, it can provide real-time, or almost real-time, insights into consumer behaviour, helping the sales and marketing teams to launch timely campaigns, products or services that can attract more consumers. Data transformation forms the backbone of several crucial processes like data integration, data migration, data warehousing, and data wrangling.

Facilitates cost saving

Poor data quality eats into the revenue of enterprises. Companies spend a lot these days trying to make the most of consumer data. Most large companies are also investing heavily in data-dependent initiatives like Artificial Intelligence and Machine Learning to get a competitive edge. However, poor data quality increases the associated costs. If used prudently, data transformation can help reduce this cost.

Conclusion

Data is gold. No doubt about it. But to make the most of it, organizations must invest in smart structuring, filtering and analysing techniques. They must equip themselves with the right tools to perform these data-centric functions and leverage these insights to make the best and most informed decisions. Those who embrace these changes will continue to innovate and upgrade their existing offerings in sync with the changing consumer needs, while those who fail to do so will be left behind and eventually turn obsolete in today's digital-first world.