Today the talk of the town in the tech space is digital transformation. Across sectors and countries, businesses and even government organizations are investing heavily in digital initiatives. The key reason is the number of valuable insights, requisite compliance, and revenue models that it can bring about besides making decision making transparent and faster. The central element of digital transformation is data, and digital transformation occurs when structured processes and digital tools empower decision makers to utilize this data to create value. The central element of digital transformation is data and digital transformation occurs when structured processes and digital tools empower decision makers to utilize this data to create value. The data may be operational data, employee data, customer data, relevant business performance data and many more. Enabling multiple systems to work with this data simultaneously and produce value is the main purpose of digital transformation. So maintaining an effective central data flow infrastructure is essential for digital transformation of any business. This is what is known widely as the data pipeline.
A data pipeline is imperative for a business model that relies on data-driven insights.
Though there are multiple ways to build and maintain your organization’s data pipeline, it should fundamentally serve two key purposes:
Empower data-driven functionalities
From simple customer data onboarding to automated customer profiling, high-end predictive data analytics, driving innovation with Artificial Intelligence to setting up IoT ecosystems, the data pipeline will be at the heart of an enterprise’s digital core making data available for use by all of its information systems.
Ensure Data Adaptability
When a gamut of systems want to access data in multiple formats and for multiple levels of processing, it is the data pipeline that ensures the availability of this data in the desired format without losing integrity. The data needs to be transformed into different modular access tokens to serve multiple purposes for the information systems that access it.
In short, a data pipeline streamlines the management of data across enterprise systems and aids in further processing, analytical mining, visualization, and structuring.
Now comes the question of building your data pipeline. For a data pipeline to be effective, the following aspects need to be kept in mind while building it:
After going through rounds of iterations, from existing systems, the data pipelines should be able to deliver the same original data and processed results with an isolated view of each for newer and external systems.
Consistent Data Management
With multiple analysis and segregation happening every second in an organization’s digital infrastructure, its data pipeline needs to deliver a consistent data management capability for best results.
Synchronized ETL Process
Multiple systems may use the data pipeline for ETL (Extract, Transform and Load) processes. A uniformity in their approach would avoid errors and ensure greater results at all times.
With these 3 aspects taken care of, it is time to pick the platform to build your data pipeline. There are plenty of options in terms of technology to build your organization’s data pipeline. Some rely on building real-time data pipelines with Apache Kafka while some belief in the power of Apache Spark to build their data pipeline. But today we look at one of the best options to build an enterprise data pipeline -Hadoop.
4 reasons why Hadoop is best to build your data pipeline
It is to be noted that organizations like Google and Facebook use Hadoop to handle their immense data management tasks and that itself is a testimony to its capabilities. Keeping that aside, today we explore 4 key benefits that made us pick Hadoop as the number one choice to build your organization’s data pipeline.
Hadoop is massively scalable across any dimension of data. Whether you want parallel processing over 100’s of microservers on different data parameters or you want to process chunks of data in bulk on single server architecture, Hadoop offers scalability and seamless control. No matter if your business wants to run hundreds of applications at thousands of data nodes, Hadoop can scale up its data management structure to accommodate the required capability.
Hadoop can work with data across sources seamlessly. Be it social media data, email conversations, images, streaming data, Hadoop can provide flexible interoperability to help businesses run their advanced data processing tools on it. They can run combined analytics on multiple data sets, provide multi-faceted insights into respective source channels and much more. This makes it suitable for creating recommendation engines, large data warehousing and transformation projects, continuous supervision and monitoring systems for fraud prevention and so on.
Today’s business systems generate data in real time and they require processing in real time as well. So your data pipeline needs to offer super-fast management of data across information systems for real-time insights. Hadoop’s unique cluster data mapping enables easier data processing even if the data is unstructured. Terabytes of unstructured data can be processed in a matter of minutes by a Hadoop system as compared to days taken by traditional RDBMS based systems.
Hadoop’s cluster data mapping also enables it to maintain copies of data across nodes in a cluster. So in the event of a node failure, there is always a backup readily available and this avoids disruptions in data processing. When you are dealing with data-intense real-time systems, this feature is critical as any minor error may result in enormous changes in delivered insights.
These are highly convincing reasons for implementing your organization’s data pipeline with Hadoop. As businesses across the globe move towards a digital future, the amount of data that they would deal with will increase exponentially. Hadoop ensures that your data is stored and managed over a future-proof platform and thus facilitates the sustained growth of your digital business. It also lays the foundation for creating newer business models that can be built on top of your data with emerging technologies like AI, Machine Learning and much more. For example, Ai powered Data intelligence platforms like Dataramp utilizes high-intensity data streams made possible by Hadoop to create actionable insights on enterprise data.
Now that you are aware of the benefits of utilizing Hadoop in building an organizational data pipeline, the next step has an implementation partner like us with expertise in such high-end technology systems to support you. Feel free to get in touch with us for building the next generation of your data-driven enterprise systems.