What’s Business Data?
Data-driven businesses are the talk of the town. What are they? And why are they of importance at all? Put simply, data-driven businesses make use of data (their own as well as those acquired from various external sources) to make informed business decisions. It may seem obvious, but it’s a dramatic departure from how most businesses used to operate. Traditionally, business decisions are made as a knee-jerk reaction to what is happening. Business managers aren’t to be blamed for this approach as companies themselves haven’t thought about using data to guide their decision-making as they, in turn, probably never had enough to do so. This is, nevertheless, rapidly changing with the rise of data science and the resulting treasure trow of customer information that many organizations either already had or have managed to get their hands on.
A data-driven business might not be the perfect fit for all occasions, but it’s much better suited to the fast-changing, modern business world than a business that doesn’t utilize data at all. It’s also something that can be adopted gradually as more data becomes available over time. A robust, feature-packed (preferably with AI & ML-powered analytics and toolsets) digital business repository is the key to leveraging the full potential of business data.
For a business to reap the full benefits of being data-driven, it is not enough to have data available. Transitioning into a data-driven organization is tough when using digital business repositories with poor system integration. Data collected from an organization’s day-to-day operations reside in various locations isolated from each other. This lack of interconnectivity in a repository between different systems brings inefficiency to the organization and only limits its capacity to successfully scale any initiative across the organization.
Business leaders need to make sure they have a repository in place where the various systems and databases that house their data are effectively connected for efficient consumption across the organization. If data connectivity and sharing are not established, it could lead to a decline in overall operational efficiency and resulting performance across the organization.
Data Multiplicity & Variety
Of the many different instances of individual data that exist, we group them into distinct types, categories, varieties, and classifications. Some of these include –
- Big Data
Big data has emerged to be defined as that amount of data that hardly fits into a conventional (relational) database for analysis and processing, owing to the huge volumes of information generated by humans and machine processes.
- Structured, Unstructured, Semi-Structured Data
All data has some structure. The delineation between structured and unstructured data comes down to whether the data has a predefined data model and whether it is organized in a predefined way.
- Time-Stamped Data
Time-stamped data is a set of data that has a concept of temporal order defining the sequence in which each data point was captured (event time) or collected (process time).
- Machine Data
Simply put, machine data is the digital exhaust created by the systems, technologies, and infrastructure that power modern businesses.
- Spatiotemporal Data
Spatiotemporal data describes both the location and time of the same event – and it can help businesses realize how phenomena in a physical location change over time.
- Open Data
The best modern digital business repositories offer support for the above-mentioned and many more data varieties.
Different Users & Accessibility
Digital repositories contain raw data (that are aimed at users across the enterprise, although often the more technically skilled users get the most value) as well as processed data (that are more useful for those operating enterprise-focused business intelligence applications within an organization).
Data scientists with specialized knowledge in working with large volumes of unstructured data are the main users of these repositories. Nevertheless, less specialized users can also utilize unstructured data owing to the emergence of self-service data preparation tools. Modern repositories allow both advanced users working on data discovery or asking hypothetical questions and anyone who needs a source of truth access to unprocessed data for reference or of confirmation.
Meanwhile, less technically savvy business analysts and decision-makers can more easily use the preprocessed data stored in these repositories. This data can also be accessed by BI tools to churn out –
- daily or weekly reports,
- charts in presentations, or
- simple aggregations in spreadsheets presented to executives.
With a digital business repository, multiple teams have access to data. Even so, there needs to be a strong focus on monitoring, regulatory compliance, and role-based access control, as well as extending meaningful experiences. A consolidated interface for configuration management, auditing, obtaining work reports, and exercising cost control is integral. When it comes to data governance, modern digital business repositories facilitate –
- easy discovery of data;
- compliance with regulatory needs;
- straightforward yet robust permissioning and financial governance structures.
As far as the security of these repositories is concerned, cloud providers have gathered knowledge and best practices from all of their customers and learned from the trial and error of thousands of other companies. Having dedicated security professionals who work to continuously improve the security of these platforms, these digital business repositories are so secure that business leaders can rest easy knowing that their data, insights, and sensitive info is in safe hands.
When it comes to storage, organizations can adopt different storage mechanisms depending upon the quantity they store and accumulate and process. Common mechanisms include –
Hadoop offers linear scalability. It has a low scalability cost compared to, say, a relational database. But Hadoop isn’t just cheap storage. It is also a powerful processing platform. And for those trying to do algorithmic analysis, Hadoop can be very beneficial.
- Relational Database Management System
The relational database management system is typically for organizations with huge amounts of data that they want to put in the repository, which is structured as well as also relational. If the data is inherently relational, adopting a DBMS approach to the digital repository would be ideal. RDBMS makes perfect sense for businesses that wish to make use of relational functionalities like SQL or complex table joins.
- Cloud-Based Storage
The global trend is moving towards cloud-based systems and especially cloud-based storage. The big advantage of clouds is their elastic scalability. They can marshal servers and other resources as workloads increase. And compared to many on-premises systems, the cloud can be inexpensive. This is partly because there is no system integration involved.
Well-designed digital business repositories bypass rigid silos and bureaucratic boundaries between business processes. Each stakeholder is entitled to access all company data if they have the appropriate privileges. They do not require data to be defined by schemas. Therefore, using one such repository leads to simpler data pipelines and faster design and planning processes.
Many organizations attempt to secure data through encryption and perimeter control but without comprehensive and granular data access control strategies. With multiple employees with different levels of authority, responsibilities, and skills performing different jobs on the platform, having such a strategy in place is key. When hundreds or thousands of employees require access to data for many other uses, crude permissions that extend to users “all or nothing” access are no longer sufficient. This is where choosing a good digital business repository that has in-built a scalable, consistent, and accurate set of control capabilities that prevent unnecessary access to sensitive information at every stage of processing is an invaluable asset to any organization.