Data intelligence is emerging as a necessity in the business world. Copious amounts of data notwithstanding, data intelligence helps businesses make sense of the quantum of data being collected.
Today, data intelligence tools come equipped with the capability to process large volumes of Big Data intelligently across various industries. However, according to Forbes, pushing Big Data aside, the concept of Small Data has been birthed recently.
Businesses aim to accelerate the generation of useful insights from high-value datasets of great significance. For this purpose, artificial intelligence is employed at various stages to achieve a high-functioning data stream.
Let’s understand the concept of data intelligence in a little more detail.
What is Data Intelligence?
Data intelligence pertains to employing artificial intelligence and its implements (like machine learning) for the analysis of unstructured data. This data is then transformed into comprehensible, meaningful insights to help align strategies and decisions with business goals and targets.
Data intelligence is comprised of five major components of data:
- Descriptive – for reviewing information and mapping performance
- Prescriptive – to model recommendations based on gleaned knowledge
- Diagnostic – for the analysis of events and trends in the data gathered
- Decisive – for recommending options by gauging values
- Predictive – to study histories and extrapolate the trends for a future trajectory
Each of these datasets delivers a unique insight that can be further utilized for decision-making. For example, the historical data of a business can reveal predictive insights, which can then be used for resource allocation planning.
In a world that is rapidly growing into a digital ecosphere, intelligent data has a big role to play in catalyzing its growth.
Why Do Businesses Need Data Intelligence?
Data intelligence relies on AI and machine learning technology to derive bold insights from a large pool of random, unstructured data that any business collects on a daily basis. The consumer is king today – and in order to deliver a better user experience and personalized services to them, businesses bank on data intelligence to generate insights that assist the delivery of quality. The same goes for business associates, partners, clients, etc.
That said, there are data privacy compliances to understand and stick to before the collected data can be perused. Privacy is big today, with cybercrime increasing hand-in-hand with digitalization.
Moreover, privacy regulations and compliance requirements vary by region – segregating and processing data while adhering to individual compliance is highly complex. This is painful for businesses running globally with audiences scattered over continents. In such cases, widely different regulations need to be complied with.
Data intelligence can maintain the required integrity when it comes to detangling data privacy complications. This way, while still being able to derive the requisite insights from the collected data, the software enables businesses to stay compliant, preserve consumer privacy, and abide by the ethics of data usage.
Data Intelligence Systems and Use Cases
Today’s data intelligence systems have evolved greatly to include many functions within their ambit. Earlier, analysts had an immense need for better tools to assist their search and discovery operations in order to create insightful reports for their businesses. This is where the use of data intelligence was mostly concentrated.
A lot more needs to be done and considered where data is concerned. This has created more use cases in the data intelligence industry, such as:
- Data migration to Cloud. AI-powered data intelligence oversees the entire migration process by monitoring ecosystem health, identifying anomalies, and flagging issues – a feat that would take forever with humans overseeing it.
- Digital transformation. Digitalizing everything is easier said than done. Using data intelligence software, processes like digitalizing documents and creating digital data repositories happen automatically.
- Compliance with regional/global regulations. Each country and region has its own data privacy requirements, which are handled by data intelligence that automatically keeps systems compliant while staying updated with the latest regulations.
- Data governance. For any growing organization, it becomes important to govern internal data to ensure security and authorized access. Data intelligence helps create versions, profiles, and other devices to this end.
- Detailed analytics, reporting, and predictive analysis. Any and every business needs insights from the data it collects. Artificial intelligence synthesizes utilizable, actionable insights from the collected data – take marketing, for example. Demography analysis, audience preferences, frequented channels, etc., can be understood with ease using data intelligence.
- Trends. Data intelligence extrapolates historical and current data to predict trends for the future.
Considering the emphasis on preserving consumer privacy in data perusal these days, data governance and compliance assume the primary priority in assuring that consumers’ privacy stays protected. At the same time, businesses can also leverage the data for important personalization, growth, and predictive insights.
How to Leverage Data Intelligence for Improving ROI
The true benefit of data intelligence, it seems, is pegged heavily on the supply of good quality data amidst the information inundation that an organization experiences on a daily basis.
Artificial intelligence and business intelligence tools can be utilized effectively when filtered data is fed into their systems after being screened through data intelligence to make the insights purer and more focused than otherwise. Let’s see how this impacts ROIs.
Empowered Decision-Making
When business tools (such as business intelligence software, CRM, or any other implements of artificial intelligence) function with more accurate and refined data, the decision-makers receive accurate, comprehensive, and concise reports. For example, resource allocation can be improved when a real-time picture of available resources is accessible at hand; data intelligence makes this possible.
Improved Operational Efficiency
With data intelligence software in place, there is no need to expend time or resources searching for a needle in the haystack. By readily getting access to the exact dataset required, organizations stand to save tons of manhours, which ultimately reflects on the ROI.
Better Data Governance
Not all employees of an organization need access to all of the company data. Data intelligence is thus advantageous as it allows filtering, masking, restricting access to, and securely storing company data in alignment with company protocol and privacy regulations.
How Secuvy Helps with Data Intelligence
It is important to identify and classify sensitive data subject to privacy regulations. To this end, Secuvy’s Data Discovery Solution makes it even simpler to identify and locate sensitive user data, classify, catalog and map it to ensure compliance with data privacy regulations at all stages.In addition, Secuvy’s Data Classification Solution helps organizations identify security and audit risks by using simple methods of data categorization, retention-related metadata, and monitoring compliance.
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