Seven Benefits of a Powerful Data Fabric
Business executives and technology leaders realise the importance of data and realise the power within massive volumes of information. On the other hand, companies often struggle to leverage the potential of big data to develop important insights since such data may be difficult to obtain, filter, and evaluate. Public sector organisations have challenges due to multiple sources and types of data, including third party data.
Data fabric is seen as a solution to this challenge. It expands on the initial ideas of a data warehouse and data lake to create an architecture that allows consistent data consumption throughout the organisation. As a result, Gartner named data fabric one of the top ten most impactful data and analytics technologies in 2021, and organisations will be driven to rethink their infrastructure to enable unique data fabric designs.
How Data Fabric Can Improve Big Data Strategy
Data fabric helps organisations achieve real economies of scale, decrease costs, and accelerate digital transformation. Organisations that have implemented a data fabric approach have discovered that analysing and managing data needs much less human intervention - between 40% and 90%. This is one reason that data fabric helps enterprises accelerate their digital transformation.
- Data fabric eliminates silos and inconsistencies - enabling "Trusted Data" to be consumed throughout the enterprise.
- Speed time to market by 80% - Because of virtualisation and auto-discovery data, it is incorporated in real-time rather than in days or months.
- Streamline and minimise infrastructure expenses – implementing controls consistently across all data reduces much of the work necessary for operations and infrastructure difficulties
- Adapt to changing situations – simple configuration allows architecture to be reconfigured quickly.
- Increase portability and reuse - businesses may create a data fabric once and then deploy it worldwide without adapting to diverse data models.
Let's look at the seven benefits of a powerful data fabric architecture.
What are the Benefits of Using Data Fabric?
1. Unlock ALL data with flexible data architecture
In most businesses, critical data is underutilised, fragmented, and inaccessible to those who need it the most. The data can come from a variety of formats and sources. There are several solutions to this issue. Approaches include using a data lake to store data in a single place with additions of both streaming and batch data.
Powerful data architecture can analyse data at the source while integrating it across cloud and on-premises systems. One of the critical properties of a powerful data fabric is its highly scalable structure.
Finworks provides flexible data architecture, bringing in a powerful data fabric. It allows you to combine all your data or utilise it wherever it originated. This could help you manage expenses with low-cost data storage and real-time streaming data input.
2. Faster time to value with data industrialisation
Data fabric is about more than simply finding and analysing data. It must also have industrialisation capabilities to operationalise the process of moving data in a robust and scalable manner.
This is accomplished with data industrialisation, which helps expedite and automate the process of extracting data from source systems, organising it in a structured data environment, and making it accessible to the end business user on the platform. As a result, the time to value from data to business insights is reduced.
The Finworks Data Platform automates the entire data pipeline enabling DataOps to provide extremely high data quality.
3. Access data from anywhere, at any time with self-service capabilities
Organisations obtain better insights and respond to changing business demands by integrating data from different sources and analysing a larger fraction of the vast amount of data generated daily. A data fabric swiftly delivers data to those who need it. Self-service helps the organisation to access relevant data more quickly and spend more time utilising that data to generate actionable insights.
- Business users have a single point of access to search, understand, modify and consume data across the organisation.
- Users can understand what the data means, where it came from, and how it is connected to other assets thanks to centralised data governance and lineage.
- Metadata management that is extensive, customisable and scales quickly. Self-service access to trusted and governed data enables collaboration with other users in the line of business.
4. Accelerate AI initiatives with faster data preparation and operationalising AI at scale
Artificial intelligence (AI) has appeared as businesses' most important strategic endeavour. Despite significant investment in AI, many businesses have yet to exploit its promise fully. One of the most critical challenges they confront is data preparation for AI and scaling up AI.
As AI becomes more central to every digital transformation project, data fabric should also handle these challenges. Finworks has effectively addressed these issues by providing assurance, accuracy and consistency of meaning through data preparation at scale. All data preparation functions are conducted directly within the platform. This helps eliminate needless data transfers, speeding up the data preparation needed for AI.
5. Intelligent data exploration enabled using industry data models and knowledge graphs
Through the deployment of industry standards, conventions and operational models, along with semantic mapping, it is possible to enable faster data integration and business change. Knowledge graphs provide the opportunity to analyse data consumption patterns, data quality metrics and operational workflow divergence.
The Finworks Data Platform provides the framework to facilitate adherence to industry data models and categorise tag data at all levels from diverse sources and formats. Thus, enabling users to create Knowledge Graphs that provide the management with a better understanding of the business, enhanced data governance and the identification of fraud.
6. Extend data fabric capabilities with partner integration
Cloud Service Providers (CSP) will help deliver many data fabric features. Extending data fabric capabilities to utilise CSP capabilities is becoming more important in the cloud era. CSPs have enabled a variety of data fabric functionalities.
Finworks data management software utilises Apache Spark and distributed or cloud file systems to achieve maximal performance. The system offers an SQL interface to the data and an interactive notebook interface for building custom dashboards and running custom Python or Scala analytics.
7. Scale data processing and analysis capabilities
By helping you extend your data processing capabilities, a data fabric can help you scale your data operations. By implementing a business facing low-code solution you can reduce the need for specialist skills. By providing a unified approach for data onboarding, data fabric helps an enterprise's digital transformation process. It reduces data integration issues, improves data quality, and simplifies data sharing and governance. It gives you a unified, comprehensive picture of your company's data, making data analysis and visualisation activities more meaningful.
The Bottom Line
Multinational organisations have already implemented multiple data models for different regions and countries. Trying to integrate AI and modern IT across various locations may be a challenging task. Data fabric, through its semantic layer, allows organisations to overcome data challenges, allowing them to realise their strategic objectives quickly.
Finworks offers data fabric solutions that are flexible, scalable and cost-effective. You get advanced data security with proven automated data compliance and cleansing. The value delivered by a powerful data fabric is critical to a successful digital transformation:
- unlocking all your data for business value
- allowing quicker time-to-value
- maximising capabilities and performance with cloud architecture
Contact us today to speak with our expert our data solutions team.