Business intelligence has undergone many changes in the last decade. Each year, we hear about buzzwords that enter the community, language, market and drive businesses and companies forward. That’s why we have prepared a list of the most prominent business intelligence buzzwords that will dominate in 2020.
Without further ado, let’s get started.
1. 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 2020. 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 at one company, it doesn’t necessarily apply at 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 future holds and create more sustainable data-driven decision-making processes throughout business operations, and 2020 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 move forward in 2020.
2. Cognitive Computing
Cognitive computing is a BI buzzword that we will hear more often in 2020. 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 2020, 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 as 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 generated revenue of $13.8 BN in 2020, it registered a CAGR of 33.1% in the last 5 years. IBM Watson is the leader in this segment, following 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 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 2020 as well.
3. Mobile Analytics
As we mentioned in our business intelligence buzzwords article for 2019, 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 2020 will increase even more. In fact, the market size is expected to reach $6.0 BN by the end of 2024, according to MarketWatch. 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 MarketWatch.
Mobility is key for growth, that is unquestionable, and companies need to realize how to implement mobile solutions which they can fully take advantage of. Quick data processing and the possibility to access data on-the-go, no matter the location, and with the only requirement of an Internet connection, makes 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, dashboards, and reports. This 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. In 2020, mobile will only expand and we will yet to see how much exactly.
Chatbots was also one of our business intelligence buzzwords for 2019, where we expounded on their general significance and expansion into industries in various forms such as virtual agents or customer service professionals. Now we will focus on what kind of analytics they could bring and disrupt the market even more.
No matter if you order a pizza while communicating with a chatbot or looking for your next holiday break, you stand a great chance to stumble upon a customer service chatbot. Their role is not just to provide you with information, but also to gather analytical data to help companies better understand their customers’ behaviors and decision-making drivers. We can safely say that chatbots will have the power to restructure business processes, enable easier communication between humans and data while ensuring that chatbot technologies such as natural language processing will bring added value to companies.
Industries such as e-commerce already have started implementing chatbots and deriving insights based on predefined performance metrics, user, message and bot metrics, just to name a few. Chatbots are not just here to, well, chat, but also to provide true analytical value both for companies and the BI community. Business intelligence has seen chatbots in the form of intelligent assistants where a question is typed directly into the software, and the software generates the answer and recommendations for further actions. Typing into a BI solution and asking a question in plain language will not just be a buzzword, but a reality that is expected to grow in 2020. We will see how vendors and companies will take advantage of chatbots more often than ever before.
5. Augmented Analytics
This data analytics buzzword is somehow a déjà-vu. Augmented analytics was indeed previously referred to as “Smart Data Discovery”. It is the combination of several data processes that, instead of just giving back data, but provides a valuable, strategy-changing recommendation. It is an approach that automates insights, using natural language generation and machine learning – and as we have seen all along this article, machine learning automation is everywhere and affecting everything, transforming the way we build, analyze and consume analytics in the future.
Augmented analytics would include augmented data preparation, but also augmented data discovery and finally augmented data science and machine learning. As Gartner explains, what is central to the development of augmented analytics is the use of machine learning automation to improve human intelligence and the understanding of the context across the whole analytics workflow. Augmented analytics will help in providing unbiased material to make better decisions and a more impartial context comprehension, and transform the way we interact with data.
Augmented analytics will also pave the way to an upcoming trend: conversational analytics. Using natural language processing (voice or text), business users will be able to explore their data, generate queries, receive and act on insight via VA or mobile devices.
6. Automated Data Wrangling
Data wrangling continues to be talked about. Data wrangling is the process of converting manually a raw format into another one, allowing thereby an easier and more convenient consumption of the data. This is a very time-consuming step of cleaning data that is necessary for any online data analysis.
Generally speaking, the data wrangling process follows 3 steps: data extraction, data wrangling, and finally, the collection of the results that will be used in the future. This is an increasingly important process to master, as the amount of data gathered and collected by organizations is not going to decrease any time soon and big data is here to stay. With the technological improvements in business intelligence in general and with self-service BI tools, data wrangling will, however, become easier and not as long and complex for IT teams and data scientists in the future.
That’s where automated data wrangling enters the picture. The process became much easier both for data scientists and companies that need to conduct this complex operation. With the help of scripts and software such as R, data wrangling is performed by algorithms and not manually by IT specialists and/or analysts. That way, wrangling is also done by using automation tools, with the goal to make the process easier and quicker as much as possible. 2020 will bring even more automation processes, and we will yet to see how it will affect data wrangling as well.
7. Self-service BI
The image of SQL experts, data scientists and system analysts working on data to extract the maximum possible is becoming obsolete. BI already helped simplifying data analysis for many business users, and the widespread adoption of self-service online BI democratized data within organizations. You can see a self-service BI interface on this example:
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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 2020 more than ever before.
User independence and self-sufficiency are in 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 2020, 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. In recent years, the level of self-service has increased and more experts predict that next year the significance will only rise This is one of the data buzzwords for 2020 that we will be hearing more about since companies are looking for ways to clean their data in the most efficient way possible.
8. 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. 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 only set to grow and this will be one of the data analytics buzzwords we will hear even more about in 2020.
Some of the simple examples of NLP usage and adoption is 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. But NLP will certainly be a buzzword in 2020, continuing its adoption in many industries and providing additional value to businesses of all sizes.
9. Data Fabric
A combination of technology and architecture that ease the complexities of managing various kinds of data, using multiple database management systems, and deployed over a variety of platforms is called a data fabric. It enables access and sharing of data in a distributed environment and supports different data management needs to deliver the right IT service level.
For years, companies have struggled to integrate all of their data into a single platform that can also be scalable. A data fabric is a simple way to achieve that goal, and this is one of the data science buzzwords that we will be hearing more about in 2020. As they expand, enterprises, organizations, and businesses of all sizes need a proper data framework to prepare and connect all the information they collect and, ultimately, extract value from it. The types of data companies collect include flat files, marketing analytics, CRM or helpdesk, for example, and the sheer number of platforms, applications and mentioned types makes it quite difficult to manage the access, processing, and integration across multiple platforms.
A data fabric will be used even more in businesses as the amount of information grows exponentially and leaders need to find proper solutions for their data management processes. We can say that data fabric is the future of data quality management, and 2020 will bring even more attention towards appropriate solutions that can be utilized in companies across the board.
10. Graph Analytics
Final on our list of business buzzwords for 2020 is the graph analytics. As Gartner predicts, the application of “graph processing and graph databases will grow at 100% annually,” and business users will find even more value in graph analysis in 2020.
The basic premise of storing, managing, and querying data in the form of a graph helps in identifying anomalies, provides faster access to data in comparison to relational databases, and simplifying complex structured and unstructured data. Visual analytics tools empower business users to perform these actions in a graphic manner, without needing to learn complicated query languages such as SQL.
Graph analytics has revolutionized business intelligence. The option to process large volumes of datasets with simple solutions such as utilizing an online dashboard enabled a more cohesive, streamlined and adaptive environment in our digital environment. We will yet see how companies will gain even more value in 2020.
We hope you enjoyed our list of business intelligence and analytics buzzwords of 2020. To summarize, we bring you the list we have discussed in detail:
- Predictive and prescriptive analytics
- Cognitive computing
- Mobile analytics
- Augmented analytics
- Automated data wrangling
- Self-service BI
- Natural language processing (NLP)
- Data fabric
- Graph analytics
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