In today's day and age where the rapidity of growing businesses has skyrocketed, their ability to manage continually proliferating data sources can make or break one. There are a lot of obstacles in the way to becoming a more data-forward organization and the path ahead isn't easy. But, fortunately, this is where data fabric enters the picture and makes life easier.
What is data fabric?
A data fabric, in simplified terms, is a composite environment unifying all the services running on one architecture. The ultimate objective is to speed up the process of data transformation by fully realizing its value.
To better understand how a data fabric is conceptualized, one can imagine it as a weave stretched across space, connecting disparate sources of information. This data from various locations and of different types can be accessed and stored easily and moves within the data fabric.
What are the principles of data fabric?
A data fabric is dictated by a set of core principles which include:
The way data is stored within a data fabric architecture has a large bearing on its performance and scale. A data fabric always provides linear scalability wherein it need not be limited by the number of files managed. It's also designed to remain consistent in its approach toward collation of data.
A data fabric is designed to effectively support a large number of data types in order to promise easy accessibility to organizations. Yet another important requirement is to provide businesses with a way to create logical separations to different facets like administration or updates.
While it is deemed necessary for a data fabric solution to give location support, wherein it can be installed and deployed successfully in any location, it's also important for it to have a sense of location awareness so that data can be addressed accordingly.
In times like today where the incidence of data breaches seems to be growing rapidly, there's more emphasis on data security solutions. It needs to be foolproof to cut down the chances of a potential data compromise. In addition to this, data backup capabilities is also a major requirement.
How can a data fabric help you?
A data fabric can help an organization to actualize its goals of data transformation and becoming a data-forward business in the following ways:
- By creating a unified environment for the process of collection of data, and thus eliminating the need for bulkier data silos
- By enabling companies to scale up rapidly by providing the necessary data applications to do so
- By making it easier to transport data across different types of platforms, whether it be hybrid or multi-cloud, which effectively translates to a faster access to quality data
- By eliminating the overreliance on age-old data infrastructures and tech solutions
While these are some of the ways in which a data fabric solution may help a business, it's worth glossing over a couple of these key advantages to make the most out of it.
Unlocking the true potential of data with flexible data architecture
In a large section of organizations, data remains unavailable and inaccessible to those in need when needed. This usually happens since data is spread across disparate source systems and in completely different formats. Companies assumed the easy way to get around this would be to throw them all in one central data lake. But, this necessitates a large amount of data movement which may not be feasible in the longer run.
A flexible data fabric architecture aims to eliminate this problem by processing data from these multiple sources and consolidating them under a single, unified environment for easier access.
Thoughtful and intuitive data exploration
The data collected is rendered obsolete if they cannot be converted into valuable business insights to help businesses make those million-dollar decisions easily. Using a complex set of data models and industry accepted practices, a highly intuitive data fabric system is able to transform data into a set of key learnings and integrate them into the business.
Yet another core competency involved in this process is data industrialization, a term that refers to automating the process of extracting data from source systems, thus making it easily available to the end user. This effectively reduces the time taken for a data to evolve into a business insight.
The future ahead will see the integration of AI which in some time will be at the core of any data transformation. Operational data can be better integrated and time to value will get further shortened.
With data management becoming more and more of a priority for businesses, it's high time that one invests in innovations like data fabric architecture to address these demands. A data fabric solution aims to provide a unified environment wherein all sources of data can be collated and accessed. It also speeds up the process of data transformation by leveraging the collected data for valuable business insights which can only take the organization to greater heights.