Relationship between data and intelligence

Difference Between Data, Information & Business Intelligence | ClicData

relationship between data and intelligence

Understanding the valuable difference between information and To establish a clear baseline, let's define information, data, and intelligence so that we and raw intelligence and begin correlation, analysis, investigation. Answer to What is the relationship between data, information, business intelligence (BI), and knowledge?. Data vs. Information vs. Intelligence. Data. (Raw facts). Information. (Original data ) . •Typically, a hypothesis states a relationship between two or more.

This is a trick question. The media succeeds in this regard because they are taking the information given to them and transforming it into a story, thus creating in some cases actionable intelligence.

What is DIKW?

What makes information finished intelligence is the analysis of information. It so happens that information is one component within this process and data another.

relationship between data and intelligence

It is important to note that intelligence is a tangible and provable product. Through collection, processing, analyzing, and disseminating of the information via this discipline, decision makers can quickly assess if the intelligence product proves to be intelligence.

The three components must collectively be true to determine that information is now considered intelligence. As evaluators and consumers of information technology, the security industry should use this definition as a standard for our expectations of the deliverables from threat intelligence product offerings.

relationship between data and intelligence

The drive for fast-paced answers from intelligence tools and providers dilutes the understanding of what real intelligence is. Right now, most organizations only receive information, because true intelligence requires analysis and production. This is because the requirements planning and direction set for automated security devices and tools are designed to limit their abilities in order to solve a certain set of problems.

relationship between data and intelligence

Everything else is discarded, knowing that a human element is required to produce actual intelligence. Tools and technology solutions are developing upgrades and advancements, but a limit to their effectiveness as a holistic solution exists today.

Fail vs Finished: The Difference Between Information and Intelligence

Defining the intelligence cycle Planning and Direction: Decision makers determine intelligence requirements based on objectives, likely in the form of a prioritized intelligence request PIR.

Sending good PIRs is essential for scaling the intelligence process. Ask only one question; Focus on a specific fact, event, or activity; Provide intelligence required to support a single decision; Are tied to key decisions that have to be made; and Supply the latest time the information is of value LTIOV.

relationship between data and intelligence

Most of the intelligence process is quite human and always will be; you cannot take the human out of the intelligence process. To keep it at scale, we constantly improve on the intelligence collections plan. Organizations should establish an Intelligence Collections Plan ICP that allows it to roadmap how the company will manage the gathering of viable information from multiple sources with varying formats of information.

Examples of cyber intelligence collections include honeypots that collect IP addresses and store the data, and human intelligence HUMINT online engagement with threat actors in online forums and chat sites.

Once raw data or information are collected, they are passed along for processing. In the automated world this is predominantly what you see in a threat feed: Processed information ready for exploitation. Once an organization has captured their needs, those needs drive collection that can be focused against the topicsthat matter most to the organization. When working on intelligence analysis and production, it is important to ensure proper tradecraft is used to reduce bias and subjectivity, increasing validity of confidence language used in any assessments.

As with definitions for intelligence, there are several versions of the intelligence cycle, but all are variations on the same theme.

File:Relationship of data, information and egauteng.info - Wikimedia Commons

The Intelligence Cycle Intelligence Production While not the focus of this writing, highlighting the Intelligence Cycle requires understanding the three key elements of intelligence production: Intelligence will only be as good as the people tasked with providing that intelligence. Personnel trained in analytical methodologies and tradecraft, who understand the importance of confidence ratings and the power of specific words when communicating, who are dedicated to objectivity, and who put integrity ahead of politics or personal gain are vital to successful intelligence.

Intelligence is only as good as the data and information available to the talent assigned. The brightest minds cannot provide intelligence in a vacuum.

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Creating valuable intelligence takes time. The best data, combined with the brightest minds, will still not produce reliable intelligence without reasonable time to process, analyze, produce, and deliver. The less time allowed, the greater the tolerance for low confidence assessments and analytic errors must be.

relationship between data and intelligence

When building a threat intelligence program, separating data, information, and intelligence clarifies what is currently available from what is needed, while simultaneously identifying what clarity is available when choosing to act upon available sources.

Using the data, information, knowledge, and wisdom DIKW model is an excellent way to understand how the elements of intelligence relate to one another. In figure 2, seen on next page, the combination of knowledge and wisdom represents a reasonable understanding of intelligence. With each step up the pyramid the user gains context and understanding, moving from a basic state of being informed to a point of understanding that can support educated decisions.

Click to enlarge Bring it All Together This is not an exhaustive look at the differences between data, information, and intelligence — only a primer.

As the concept of intelligence gains in popularity in the private sector, so grows the need for a shared understanding of what it means to ask for intelligence to inform decisions. They are points of information that can be acted upon, but offer little beyond that transaction and bring an organization no closer to the understanding needed to push from a reactive to proactive state.

The Differences Between Data, Information, and Intelligence | United States Cybersecurity Magazine

Intelligence, produced through a reliable and repeatable process — by personnel specifically trained to conduct such work — is what makes sense out of chaos. Intelligence helps leaders understand the quantity and quality of the information analyzed, puts that body of inputs into context and connects dots and prioritizes actions. Intelligence empowers leaders to make reasoned and informed decisions that align with organizational needs and objectives.