Top 10 Business Intelligence Trends
Today, business intelligence solutions have a quite important and popular place in order to make healthy forward-looking decisions and to get ahead in the analytical competition. Deep exploration of data, combined with smart technologies, helps companies quickly shape their futures while taking them to the next level. Topics such as marketing campaigns, consumer loyalty and retention, new financial opportunities and operational efficiency are just some of the benefits of business intelligence. Trending applications in business intelligence are for these benefits to reach the maximum point. It is clear that the time and effort between data and decision making with the widespread trends will shorten significantly.
1. Artificial Intelligence & Machine Learning
It is aimed that people will understand their data more accurately and quickly, thanks to the machines that automate decision making. Artificial intelligence (AI) and machine learning (ML) are not yet common enough in business intelligence. The reason for this is that the answers given by artificial intelligence cannot be explained clearly. In order for these practices to become widespread, they must be transparent and reliable. Many data science tasks will be automated in the coming time. Machine learning will help skilled analysts with insights that they even find difficult.
Artificial intelligence will be able to detect any unusual or significant change in data patterns soon, regardless of the size and complexity of data sets, and organizations will only need to input raw data. Many organizations have embraced the value of artificial intelligence and machine learning.
2. Natural Language Processing
Natural language processing (NLP) is the structure that allows people to chat with data by bringing together computer science and linguistics to help the computer understand the meaning behind the human language. Thus, a person can ask a business intelligence tool to “find major earthquakes near Istanbul” or “find those near Mugla” and get the answer to these questions based on data visualization. With machine learning within the scope of modern business intelligence, systems are provided to have deeper knowledge over time, according to the data of a company and the type of questions asked by users.
3. Augmented & Smart Analytics
Augmented analytics is a form of data discovery that automates data understanding by using machine learning (ML) and natural language processing (NLP) — natural language understanding (NLU) and natural language generation (NLG), which are sub-sections of NLP — to improve data analytics, data sharing and business intelligence. With the increasing raw data, data preparation, classification and analysis will become automatic. Hence, with increased analytics, it is aimed to make less biased decisions and to enable users to interact with data more.
4. Digital Assistant
Everyone who works with data will be equipped with “voice-operated” digital assistants created over time with the help of artificial intelligence and natural language processing. Voice-activated virtual assistants such as Siri and Alexa will begin translating the language into text and transforming it into structured data to be analyzed for foresight. A serious increase in the use of smart assistants is expected in the coming years.
5. Actionable Analytics
Business intelligence platforms ensure that everyone who works with data stays in the process and flow by combining the business process and workflow with mobile & embedded analytics and dashboard extensions. Actionable analytics speeds up the decision-making process for all technical and non-technical roles. In this way, data workers can take action quickly after analyzing the data and discovering a foresight.
Users do not need to point to another application or a shared server as embedded analytics reveals analysis and insights more accessible to them. Mobile analytics offers these features to all users regardless of where they are physically located. Analytics can only be applied by giving the right message to the right person at the right time.
6. Data Management
Data Management is the practice of organizing and maintaining data processes such as obtaining, verifying, storing, protecting and processing. As data sources increase in number and have more complex structures, data management is becoming extremely critical in business intelligence. Thanks to the correct management of data, data security is ensured, risk and compliance processes are supported, problems in data quality are eliminated and operational efficiency increases. Therefore, it is of great importance for companies to manage their data effectively and in accordance with corporate data models in order to ensure their sustainability.
7. Predictive Analytics
Thanks to predictive analytics, we can have an idea of where an industry will go with data such as “what people buy, what they respond to, what they like or don’t like”, or a cyber-security expert can use predictive analytics to detect fraud or cyber-attacks while they are still at an early stage. You can make your risk assessment analysis accurately with predictive modelling. So you get reliable predictions in future scenarios.
8. Data Value
We know that the world’s leading brands such as Facebook and Google make money from the data they collect from users. When we evaluate business intelligence trends after 2020, it can be predicted that companies will use their data to identify new revenue opportunities. Thus, regulated data trading may be the profession of the future.
9. Data Storytelling
When the actions taken to discover and share important points in the data are combined, “data storytelling” emerges. Storytelling has become a critical part of the analytical process, as the data is truly understood, allowing people to participate in the analytical conversation. Thus, data literacy efforts are also supported. In addition, narrating the data makes it easier for analysts to approach the result and ensures that the desired message is conveyed to the other party in the most effective way. In the speech that starts around the data, the audience is positioned at the center of the conversation. This is why data storytelling has become the new communication language of companies.
10. Cloud Migration
Data will be moved to the cloud at an increasing speed and this situation will cause companies to review their data strategies. Storing data in the cloud provides companies with many advantages such as low cost, ease of access, security, flexibility and scalability. In addition, the cloud creates an accurate resource by making it possible to share secure dashboards with business partners or customers. Many companies around the world are experiencing hybrid solutions (private & public cloud) to take advantage of various data sources. We will observe that multi-cloud strategies are becoming dominant in the coming days.
The benefits of business intelligence in optimizing time and directing work are not discussed. That is why business intelligence is taking over the world rapidly. In order for your company strategies to be successful in a competitive environment, you need to follow the trends in business intelligence regularly and add new business intelligence solutions to your life. Remember that data never lies. Therefore, it is inevitable to go to a solid solution with the insights you reach. Organizations can easily improve their business processes and work-flows by being aware of all of them.
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