Data fabric has recently become one of the most common terms to make rounds on the internet. Gartner’s study, a global research firm, pointed out data fabric to be one of the “Top 10 Data and Analytics Technology Trends”. So now you might be wondering what data fabric is and why it is so important for companies.
Simply put, data fabric can be defined as an end-to-end data management and integration solution consisting of integration architecture along with technologies or services running on that architecture. Its aim is to promote digital transformation by multiplying the value of your data.
Let’s dig deeper and find out a little more about data fabric and how it is modernizing data management.
What Is Data Fabric?
Data Fabric can be considered a data management solution consisting of architecture, data management, and integration software. It stores all the data in a single place, cleanses and then processes it.
Data fabric is architectured and designed in a way to decode complex problems and manage data more desirably. It also promotes effortless access and sharing of data in a distributed ecosystem.
Why Is Data Fabric Important For Businesses?
With the coming of the internet, the world became a more connected place as it gave individuals a chance to connect with their near and dear ones irrespective of where and in which time zone they live. However, the internet is used for so many other things other than communication in today’s world. Therefore, it has become a major platform to carry out activities that are beyond initial forecasts in which data is the only fuel.
The quantitative activities conducted on both digital platforms and real life can be designated as providing data. With the growing amount of data, it is necessary to develop an infrastructure that can handle and process them.
Previously, the ultimate goal was handling data and extracting valuable insights from them. However, the focus is slowly shifting from just handling data to providing valuable insights. The emergence of data fabric has helped in handling data efficiently, improving the quality, extracting more information from internal and external resources and deriving beneficial insights from it.
Use Of Data Fabric In Modern Businesses
The number of businesses, entrepreneurs, and companies penetrating the networked setting has skyrocketed recently. Since the internet became accessible to everyone, all websites have become a source of data. Because of this reason, it has become extremely important to increase the value of these data. However, a few problems are hindering the process of increasing data value, which is as follows:
- Data is stored on different file systems, SaaS applications and storage systems.
- There is no universal format of the available data. They are all available in different formats.
- The database consists of both unstructured and structured data.
- Data is stored in different platforms having different scenarios.
- Data is located at multiple on-premise locations and clouds.
All the above challenges point out that data is growing at an exponential rate. These hurdles make it extremely difficult to access data and extract insights from it. If any business or company wants to specialize in delivering ML, big data solutions and AI, they need to collect, structure and process their data. Most businesses tend to tackle this problem in warehouses by administering data throughout the enterprise by developing different ways. While this solution works great in multiple teams, a lot of data gets forgotten and sits idle when it comes to accessing data throughout the enterprise.
The data usage and accessibility challenges lead to lower productivity and a lack of credible data to gain insights for making future predictions. The solution to solve all these problems is data fabric. It helps businesses to gather credible data from the complete network and analyze them thoroughly to gain valuable insights.
How To Implement Data Fabric?
Data fabric begins with online transaction processing, where data relating to all transactions is combined, updated and stored in warehouses on a database. This data is then processed, structured and cleansed for further use. Any person who has access to the data can use it for deriving insights to help the business adapt and grow.
Implementation Of Data Fabric Requires
1. Applications
The correct infrastructure, which includes GUIs and applications to acquire data, is created for clients to communicate with the organization.
2. Developing the right environment
It is important to develop the right environment to collect, handle and store data.
3. Security
All the data collected from external and internal sources must be secured.
4. Storage
All the data collected needs to be stored successfully and efficiently. It must also be easily accessible and allowed to scale when required.
5. Transport
It is important to develop the right infrastructure to access the data from any location in the organisation.
6. Endpoints
Build the correct software that would help to extract valuable information in real-time.
Conclusion
Data fabric is most suitable for geographically scattered businesses with more than one source of data and experience complex data-related problems. However, it is important to remember that data fabric isn’t a substitute for data processing and integration. For that you will need to make use of data virtualization.
Globalization is slowly spreading its roots in remote areas with improved hardware capabilities. In addition, data connectivity is speeding over the roof, overwhelming companies with huge volumes of data from both devices and services.
To solve these problems, companies can turn to data fabrics because it provides:
High compliance and integrity to regulations while offering a real-time flow of data and accessibility.
An agile model is enabling changes, adapting per the requirements and functioning across all systems.
Minimum training and scalability with no interference.
The massive volumes of data that the companies access need to be examined and analyzed to gain valuable insights. Sectors like marketing, user behaviour, supply chain optimization, forecasting and sales offer a competitive lead to businesses.
