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BI Buzzwords

BI Buzzwords

1. X Analytics 

X Analytics is a term coined by Gartner and it refers to the X variable for «different structured or unstructured content such as text analytics, video, and audio analytics,» among others. The «X» stands for any type of analytics like the one mentioned, which will trigger disruptive changes in 2022 since many companies still don’t leverage enough various possibilities that analytics have on offer. But on the other hand, we see businesses adopting these new opportunities through online data analysis, where business users and analysts don’t have to utilize heavy IT technical capabilities but on the contrary, analyze the data on the fly, no matter the location or device. 

These analytical solutions have developed in the recent decade as new, powerful software has entered the market and made businesses more intelligent than ever before. For example, innovatory BI solutions created opportunities to utilize AI to explore data, connect the dots, and identify new business opportunities. By enabling users to analyze and interpret the data on their own, with the help of smart analytical solutions, companies have added analytics as the backbone of their strategic development. 

Not only visible in business, but in society as a whole, where public health experts have used multiple sources this year to identify the best possible solution for disease management and help vulnerable populations. Planning capacities, finding new treatments, and controlling Covid-19 have been influenced by AI and its capability to comb thousands of research papers, social media posts, news sources, etc. That said, this is one of the data analysis buzzwords we will definitely hear more about in 2022. 

2. Decision Intelligence 

Continuing our list of data buzzwords 2022, decision intelligence is certainly one worthy point to include since businesses of all sizes must embrace the power of generating actionable insights and make better decisions through data and analysis. In recent years, companies have started to adopt solutions such as self-service BI, that foster the decision intelligence roadmap: observe, investigate, model, contextualize, and execute. This model has become increasingly important in today’s competitive environment, where countless pieces of information are being generated but the quality of decision-making can suffer. 

But let’s get back to basics. Decision intelligence offers a «structure for organizational decision-making and processes» with the help of machine learning algorithms. It’s a field that includes also methods such as descriptive, diagnostic, and prescriptive analytics. Moreover, it contains 3 types of models: human-based decisions, machine-based, and hybrid decisions, each with its own set of characteristics with data being the core force. But, as we all know it, humans cannot process so much data on a daily basis and expect positive business outcomes. That’s why artificial intelligence supports managers in their path to successful data-driven decision-making and helps them to make accurate, fast, and fully informed business decisions. 

In practice, decision intelligence is one of the business buzzwords 2022 that has evolved and will evolve companies in different industries. For example, a bulk carrier in the US used IBM to optimize their logistics processes and transportation, resulting in millions of dollars saved. The smart decision-processing method enabled the company to save unnecessary driving and optimize routes in real-time. Another example comes from the banking industry, where decision intelligence helped transform their telecommunication technology into a more advanced one and saved countless dollars. Their database was extremely large, and the updates would cause a chain of events that could affect many other parts of their system. Thanks to the cause-and-effect link of decision intelligence models, the bank managed to upgrade its systems seamlessly. 

3. Data Fabric   

The number of sources from which businesses gather data is increasingly growing. As this grows, so does the need for faster access to information that is distributed in several locations. That’s where data fabric comes into the picture to establish itself as one of the most important BI buzzwords of 2022.  

Gartner defines data fabric as a “design concept that serves as an integrated layer of data and connecting processes”. Putting it in simpler words, data fabric is a data management architecture that aims to help organizations access and connect data from multiple types, locations, and sources in order to close the breach between the data available and the knowledge extracted from it. This allows businesses to access their data faster and in a structured way, from collecting, ingesting, and integrating. The data can also be shared with internal or external applications and used for a number of scenarios such as product development, sales and marketing optimization, and more advanced processes such as forecasting.  

The main reason why data fabric will be so useful for businesses in 2022 is that it will help them extract the full potential out of the information available. Studies say that organizations only analyze 12% of the data they have, meaning 88% of valuable information is left unseen. With a data fabric strategy in place, from average business users to data scientists will have fast and compliant access to all the needed data for an improved decision-making process. Like this, businesses can simplify data management, governance, and automate several processes in a complex multi-cloud environment while cutting costs and risks.  

The goal of data fabric is simple. Providing a single environment for all the available data, from any location, to ensure an optimized and unified data management process. It’s about leveraging people and technology to maximize the value of their information. Allowing them to produce more engaging customer experiences, better products, and services, and increase overall business efficiency.  

4. Digital Automation 

The umbrella term of digital automation focuses on the rise of intelligent technologies to have an impact on businesses across industries, providing automated processes that make big data and analytical analysis easier to utilize and comprehend, and, consequently, gain valuable insights. Integrating artificial intelligence and intelligent automation tools to solve business challenges while increasing productivity will become a pivotal point in the next phase of digital transformation

The importance of speed in businesses is not the latest news, but the tools and means to gain proper data, be it while compiling a management report, determining which KPI examples to research, study and choose, or which AI automation process to leverage in a specific industry, will certainly affect businesses of all sizes in 2022. 

Taking advantage of artificial intelligence and machine learning while using neural network alerts and pattern recognition alerts, can bring automation for a business on a speedy, valuable, and sustainable level. And since a giant like MIT is investing in a new college focused on AI worth $1 billion, we will keep digital automation as one of the business intelligence buzzwords to look out for in 2022. 

5. Data Catalogs  

As businesses work with larger data sets from several sources, the need to keep all the information organized for an efficient data management process becomes critical. For this purpose, the use of data catalogs will rule in 2022 as one of the prominent buzzwords for data analytics.  

In simple terms, data catalogs are an organized “inventory” of your data that is done after the mapping process. By using metadata, catalogs help businesses to manage their datasets and keep them organized to facilitate the access and collection of relevant data from any of their storage locations, be it cloud storage, warehouse, or any other. Think of it as having a universal catalog for all the libraries in the country, all you need to do is access the catalog, look for the book you want, and access all the information available on it. That’s what a data catalog can do for a business.  

When used correctly, data catalogs will give you the flexibility to extract insights from large amounts of data in an efficient way. Having all your data sets organized in catalogs will make browsing through all the information a fast task. Data catalogs provide visibility making it easy to find and evaluate relevant data from any storage location. 

As mentioned, the basis of a successful data cataloging process is to take advantage of the metadata. You can use software to crawl your databases and gather the needed information from your storage locations. And, after you have the needed metadata, you can build a dictionary that will serve as an index to identify and retrieve the needed information. A data dictionary is also a useful tool for non-technical users as it helps them recognize the relevance of the data without going too deep into it.  

Cataloging your data not only keeps everything organized but also helps you stay compliant with privacy regulations. You can set up labels that relate to data privacy and retrieve the data in a compliant way. Additionally, data catalogs will help businesses to focus on the most relevant and updated data, this will also ensure that everyone is working with quality data for their reports and analysis.  

All of this, paired with the fact that businesses are collecting more and more data every day, makes data catalogs one of the most interesting business intelligence buzzwords for 2022. Using data catalogs to your advantage can help you save costs, increase your operational efficiency, provide a better customer experience, and gain a competitive advantage.  

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6. Predictive & Prescriptive Analytics 

 Predictive Analytics: What could happen? 

We mentioned predictive analytics in our business intelligence trends article and we will stress it here as well since we find it extremely important for 2022. Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. Applied to business, it is used to analyze current and historical data in order to better understand customers, products, and partners and to identify potential risks and opportunities for a company. Without a doubt, it’s a big technological advancement, and one of the big statistics buzzwords, but the extent to which it is believed to be already applied is vastly exaggerated. 

The commercial use of predictive analytics is a relatively new thing. The accuracy of the predictions depends on the data used to create the model. For instance, if a model is created based on the factors inherent in one company, it doesn’t necessarily apply to a second company. The same may be true about a model for one year compared to the next year within the same company. Approaches need to take this dynamic nature into mind. Moreover, as most predictive analytics capabilities available today are in their infancy — they have simply not been used for long enough by enough companies on enough sources of data – so the material to build predictive models on was quite scarce. 

Last but not least, there is the human factor again. The psychological patterns behind why people make decisions cannot be boiled down to simple logic and very often are complex and unpredictable. 

Nevertheless, predictive analytics has been steadily building itself into a true self-service capability used by business users that want to know what the future holds and create more sustainable data-driven decision-making processes throughout business operations, and 2022 will bring more demand and usage of its features. 

Prescriptive Analytics: What should we do? 

Prescriptive analytics takes the next step but also analyzes and includes action. These analytics use optimization and simulation algorithms to advise on possible outcomes and answer: “What should we do?” This allows users to “prescribe” a number of different possible actions to undertake and guide them towards a solution. Prescriptive analytics attempt to quantify the effect of future decisions in order to advise on possible outcomes before the decisions are actually made. At their best, prescriptive analytics predicts not only what will happen, but also why it will happen. The analytics also provide recommendations regarding actions that will take advantage of the predictions. We are excited to see how prescriptive analytics moves forward in 2022. 

7. Cognitive Computing 

Cognitive computing is a BI buzzword that we will hear more often in 2022. Considered a new big buzz in the computing and BI industry, it enables the digestion of massive volumes of structured and unstructured data that transform into manageable content. It mimics the human brain and is creating a path to technologies that will imitate human information processing on a more sophisticated level than ever before. Companies can use algorithms within BI tools to identify consumer behaviors, trends, and patterns, and in 2022, we will hear even more success stories about this interesting buzzword. 

With technologies such as natural language processing, machine learning, pattern recognition cognitive computing is considered a next-generation system that will help experts to make better decisions throughout industries such as healthcare, retail, security, and e-commerce, among others. With the expected total generated revenue of $87.39 BN this year, it will reach a CAGR of 31.6% by 2026. IBM Watson is the leader in this segment, followed by Google and Facebook that are rapidly building systems to tackle this market. 

One example in business intelligence would be the implementation of data alerts. Based on technologies such as neural networks, already mentioned pattern recognition, and threshold alerts, the software notifies the user as soon as a goal is reached or a business anomaly occurred. This is just the beginning of the computing possibilities that are already becoming a standard in business operations. Other examples include brain-machine interfaces, robotics prostheses, robotic assistants, autonomous cars, and many more. These systems can already speak, write, read, and learn; hence, this is one of the big data buzzwords that will continue to disrupt industries in 2022 as well. 

8. Mobile Analytics 

Mobile usage is becoming an increasing factor in BI. With more vendors each year that offer mobile solutions within their software, companies are also starting to implement mobile data management and 2022 will increase even more. In fact, the market size is expected to reach $6.0 BN by the end of 2024, according to Research Nester. That only proves how this is one of the analytics buzzwords that is going to continue its growth and market expansion. While North America accounted for the major share in the mobile analytics market, Europe and the Asia Pacific are going to witness lucrative growth as well, states Research Nester. 

Mobility is key for growth, which is unquestionable, and companies need to realize how to implement mobile solutions that they can fully take advantage of. In the business intelligence world, mobile analytics means providing users with the ability to quickly access their data on the go, no matter the location, and with the only requirement of an Internet connection. Like this, users are empowered to leverage their data from wherever they are with the same features they would have on the desktop, making mobile analytics an added value to businesses across the globe. Giants such as Amazon, Google, IBM, and Yahoo have already been identified as key players, confirming the importance of mobile in today’s competitive digital world. 

Why is mobile becoming pervasive can be simply explained by the rapid expansion and implementation of tablets, laptops, and mobile devices on which users can access analytics easily, without the need of being physically present in a company. Anyone can access their analytics data with a business account and simply log in to a cloud service, for example, and gain instant insights on the performance, numbers, online dashboards, and reports. The most common use cases for mobile BI are through a webpage in which users just need to log in via their personal account, an HTML5 site that works similarly to a web page but with some improvements such as not relying on proprietary standards. And lastly, one of the most complicated and expensive ones, via a native app that can be downloaded into any mobile device.  

Mobile analytics is becoming a huge advantage for companies since they have the opportunity to make faster decisions, answer business questions immediately, and conduct an instant analysis of data while providing access to everyone who needs it. In 2022, mobile will only expand and we will yet to see how much exactly. 

9. Self-service BI 

The image of SQL experts, data scientists, and system analysts working on data to extract the maximum possible are becoming obsolete. BI already helped simplify data analysis for many business users, and the widespread adoption of self-service online BI democratized data within organizations. By using technologies such as drag and drop interfaces and interactive visualizations in the shape of business dashboards, self-service BI opens the analytical doors to anyone who wants to use data for their decision-making process with no training needed. You can see a self-service BI interface in this example: 

Automated business intelligence increases that process and will make BI accessible to anyone and everyone: it will no longer be restricted to small groups of specialized people, and “citizen data scientists” will become the norm. Modern BI means less specialization, more automation, and an easy approach to data analytics for everyone. 

By creating more streamlined processes to dig deep into business data, productivity will increase, and it will also help in overcoming the skills gap. Business intelligence will hence become more accessible, democratizing data in 2022 more than ever before. 

User independence and self-sufficiency are at the heart of self-service BI. The usage of information within a company will bring even more decentralization of data and accessibility for everyone. But the level of decentralization also depends on the requirements and user roles – while it can help fulfill various tasks, it certainly needs to be considered which ones and for whom. In 2022, we will see more vendors taking the role of providing tools that can be used by everyone in the company – analysts, departmental managers, or average business users. 

Before the self-service approach in BI, companies needed to hire an IT or data science team to perform complex analysis and export data reports. This became a huge setback as the need for more agile reporting and analysis increased. With self-service solutions, users from all levels of knowledge are empowered to work with data, generate reports with just a few clicks, and extract actionable insights to boost performance. In the next few years, the level of self-service is expected to evolve and experts predict that next year the significance will only rise. This is one of the data buzzwords for 2022 that we will be hearing more about since companies are looking for ways to clean their data in the most efficient way possible. 

10. Natural Language Processing (NLP) 

Natural language processing is transforming business intelligence at a remarkable pace. And not just NLP, but all of its manifestations such as natural language understanding (NLU), natural language generation (NLG), or natural language interaction (NLI). Each has its foundation in artificial intelligence solutions developed to make human-computer interaction easier and more efficient. NLP is a developing field that catches the attention of experts from all over the world. In fact, for December 2021 the 2nd International Conference on Natural Language Processing and Computational Linguistics is expected to be conducted in Beijing, China. There, it’s expected that experts from all over the world will share their knowledge, findings, and projects regarding NLP. 

But, before we continue, what is really NLP? Essentially, Natural Language Processing is a subfield of computer science and AI that gives computers the ability to understand any form of human communication be it text or spoken words. The basics lay within complex computational and mathematical methods within the machine learning domain, and the development started almost 50 years ago. Traditionally, NLP has seen the most success in facilitating text analysis but the applications of NLP will become even more accessible to the average business users and their everyday utilization of BI. 

Business intelligence is changing the way we interact with natural language processing, especially in large datasets. It enables non-technical users to perform complex analysis with the help of software, and without the special intervention of the IT team. NLP helps in revealing patterns that could otherwise stay uncovered so it’s not a surprise that the industry expects to grow with a CAGR of 18.78% by the year 2023. The communication capacity of cognitive computing will not stall but is only be set to grow and this will be one of the data analytics buzzwords we will hear even more about in 2022. 

Some of the simple examples of NLP usage and adoption are autocorrecting, machine translation, bots, virtual assistants, and not to forget giants such as Siri or Alexa. In business intelligence, one of the popular usages is in the form of opinion mining. Big brands use NLP techniques to perform social media monitoring to help in the analysis and reflect customer sentiments. For example, to measure whether the reception of a new product is good or bad. Another common use when it comes to data analysis is to clean the data by using a method called stemming. Essentially, this method uses algorithms to reduce words into their most basic form. For example, if your dataset has the words changing, changes, changer, they would all be turned into the simple form change. This keeps the analysis process clearer and faster. All things considered, NLP will certainly be a buzzword in 2022, continuing its adoption in many industries and providing additional value to businesses of all sizes.