More and more business organizations throughout the world are realizing the importance of data. It is due to this reason that the number of CDOs (Chief Data Officer) is quickly rising. In 2010, there were only about 15 CDOs. But by 2020, it is expected that there will be more than 10,000 CDOs. This clearly shows the impact data has on organizations.
To facilitate the transformation of your organization to a learning one, there is a crucial need for a deep understanding of various technologies. Data volume is only likely to increase. However, data collection or management is already becoming an outdated concept, and the world is moving towards data intelligence. Businesses know that data is at the center. It can be used for a digital transformation of the entire organization. Hence, businesses are investing heavily in data intelligence.
Business processes can be optimized with the help of data. Data intelligence enables businesses to make better decisions as it shows historical and present data related to the particular context. It is leveraged by analysts to offer competitor and performance benchmarks to ensure that the organization runs more efficiently and smoother.
Market trends can be easily spotted by analysts to boost revenue and increase the profit margin. From hiring to compliance, data intelligence has various applications. It has the potential to help the business in all its efforts. Some of the ways through which data intelligence can be used to make data-driven and smarter decisions are mentioned below.
- Helps discover problems or issues regarding a wide range of situations.
- Effectively spots market trends.
- Predicts the success of a product or service.
- Optimizes operations
- Tracks the performance of a product or service.
- Compares data with major competitors in the market.
- Analyzes customer behavior to provide actionable insights.
- Identifies different ways through which profit can be increased.
How Does Business Intelligence Work?
Every business organization has objectives. To meet these objectives, performance is measured against these objectives. In order to measure performance, necessary data has to be gathered, analyzed, and the course of action that needs to be taken needs to be determined to meet those objectives. Normally, data is stored in a data warehouse. After it has been stored, the data can be accessed by users. It is the first step of process.
Data intelligence includes business analytics and data analytics. They are not the only tools that are used. Data intelligence helps provide meaningful conclusions from data analysis. Predictive analytics and advanced statistics are used to forecast the future patterns and to discover patterns that impact the business at present.
Data intelligence uses algorithms and models to provide results in an actionable language. Data analytics are conducted by businesses in order to form the overall intelligence strategy. It helps answer specific questions and offers an analysis for planning and decisions.
Data analytics can be used to improve the business operations continuously. When it comes to data analytics, it is important to keep in mind that it is not a linear process and only offers more questions that need to be inquired further. The process should be considered as a cycle of information sharing, exploration, discovery, data access, and more. It is often referred to as a cycle of analytics.
Types of Data Intelligence
Organizations collect different types of data for various purposes. These help offer actionable insights.
Big Data
Data is produced in huge amounts continuously by companies. Although the name Big Data might imply data quantity, it refers to a lot more. Big Data is not about having a huge quantity of information but rather using that data for various analysis. It is the most popular buzz word these days. Big Data helps structure data that is unstructured.
It provides actionable insights for decision making. In order to perform reliable analysis, data has to be structured. Structural architecture needs to be in place to handle the large flow of data. Thus, it is possible to perform analysis more accurately and efficiently.
Data Mining
Once large sums of data have been stored, Big Data will be used to analyze it. Data has to be grouped and differentiated into different categories before insightful and relevant information can be obtained. Data mining is a vital process wherein huge sums of data is analyzed to find patterns that are categorized to provide help in future analysis.
Data is assembled into categories and stored for further use in intelligent methods. Future trends can be predicted using data mining. When there is a need to predict consumer behavior, data mining is the most useful technique as it helps uncover crucial information.
Event Processing
Beneficial conclusions have to be acquired after the data has been categorized. Event processing is used to achieve this as it processes information after it has been tracked from events which provide data. It allows for patterns and important events to be predicted. Important events include business opportunities, whereas, negative events could be security threats or increased competition. Hence, there is a need for a system to conduct event processing.
Online Analytics
Web data can be captured and measured with the help of online analytics. Business rely on online analytics for measuring the online traffic and for conducting market research such as the identification of a niche. Moreover, the effectiveness of online presence, online campaigns, site performance, brand awareness, and similar operations can be tracked with online analytics. Customer experience can be improved by using online analytics as it is a great source of data intelligence.
Web traffic and customer behavior is analyzed to find patterns and ways through which more customers can be attracted and to better retain customers. Google analytics is commonly used for online analytics.
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