Developments in the field of business intelligence of BI as it is popularly abbreviated have been nothing short of revolutionary in the past decade with the explosion of data and the emergence of Big Data. Additionally, the Cloud has become available to almost all connected households. We finally got to say goodbye to spreadsheets and welcomed in data visualization that is teeming with insights along with business dashboards which are interactive as well. Another important development is the fact that self-service analytics is gaining popularity which in turn is making the data product chain more democratic and accessible to the layman.
BI got to witness some really big developments in 2020. The visible trends this year is likely to spread out across much of the coming years as well. BI is a field whose landscape is undergoing constant evolution. Here are the top 3 ways in which BI is likely to shift towards:
Data Quality Management (DQM)
Data quality was one of the predominant themes in the field of analytics this year. BI underwent developments in the analysis of data from innumerable sources and the extraction of value from the same on a large scale. This led to several errors along with reports whose quality was often questionable. Added to it was the complexity brought in by the existing disparity between types and sources of data making the process of integration even more convoluted.
It was of little wonder therefore that a particular study carried out by Business Application Research Center found that DQM was the single most important trend to watch out for in 2020. This reaffirms that apart from the quantity of data the use context and data quality and its interpretation stand firm as the primary focus of BI in the near future.
As a result management of master data is being increasingly prioritized in the overall BI strategy of the organization.
Most businesses these days recognize how big an impact data quality has on its analysis and in turn on its effectiveness in the whole process of making decisions. Accordingly, they are adopting DQM policy, techniques and even departments to implement the same. DQM assumes its importance form the fact that it is key to effective analysis of data. Gartner estimates that businesses lose out on $15 million each year on average. Bad quality data often has disastrous consequences which might range from inaccuracy in customer understanding to even inaccuracy in the presentation of the right decision to make regarding businesses. This is one of the main reasons why it is so vital to choose the right KPIs for the correct evaluation of business performance as there is no want of examples of KPIs being affected by the success of failure of data management process’s quality.
DQM comprises the processes of acquisition of data, implementation of data processes that are fairly advanced, effective distribution of the data and the management of oversight data.
SQM is by no means solely on the upswing in terms of 2020’s BI trends but rather is becoming a key practice adopted by businesses for their bottom line. Also, the demands, as well as the compliance regulations of recent times, make maintaining strict levels of data quality imperative. When this DQM is implemented company-wide, businesses stand to better use BI which results in better ROI for BI in addition to giving the organization a competitive advantage.
Discovery or Visualization of Data
The Impact of data discovery continued its upward trend in terms of importance last year. The survey we referred to earlier in this post found it to be among the top 3 BI trends from the point of view of importance. The trend of the empowerment of business users through data remains consistently strong.
One of the most important things to consider is the tools used for data discovery are dependent on a process and only then will they bring business value with the results. This calls for an acute understanding of the relationship between guided and advanced analytics with data and its preparation and analysis in a visual way. The demand for data discovery tools only points towards the increased importance of using data and deriving insights from the same. For such insights along with a decision-making process that can be sustained online data visualization tools have proved to be an invaluable resource. Such software needs to have the following characteristics:
- Ease of use
- Flexibility along with agility
- Diminished time to insight
- Can handle a large variety and volume of data with ease
For businesses irrespective of their size, the tools that let them discover business operation trends or facilitate immediate action upon a business anomaly, are becoming truly invaluable.
Due to the better processing of visual data by human beings, the trend going for data visualization in BI is likely to persist to 2020 and on wards.
Gartner in its 2020 report on Strategic Technology Trends chose AI as one of the most important ones. It speaks of the combination of AI with hyper-automation and autonomous things with special attention paid to AI security with the latter developing attack points which it is vulnerable to. AI is the science meant to let machines carry out tasks that could erstwhile only be possible conducted by human beings. Even though it could indeed be a potential threat, in truth Artificial Intelligence is far from being that developed.
Machine Learning working at tandem with AI are causing an immense and revolutionary change in the way people interact with analytics and management of data along with incrementally adding to the security.
Analytics in business organizations is witnessing an evolution from passive mainly static reports of what has already taken place to live dashboards that gives business users a real-time glimpse at things along with helpful alerts whenever an anomaly is detected. AI algorithm-based solutions making use of advanced neural networks can detect anomalies with really high accuracy because it learns from historical patterns as well as trends. This means that all unexpected events will be registered by the system with immediacy along with notifications to the user.
Another key area where AI is particularly useful is its ability to come up with enhanced insights. In its essence, what it does is a full analysis of the data-set on its own without the business user needing to intervene. All the user has to do is to pick out the source of data intended to be analyzed along with the variable or column the AI should concentrate on. This will result in automatic calculations and you will end up with the trends or growth or forecast reports, the important segment correlations, the value driver as well as the anomalies in addition to what-if analysis. This results in increased automation and saves precious time as the tasks earlier handled by data scientists will be done by a tool while providing the user with insights of high quality along with enhanced comprehension of the information even if the person is not strong in IT.
Not only that AI assistants let users communicate with software in plain human speak.
The need for online real-time data analysis tools is becoming greater and the IoT era which will bring with itself almost infinite data will serve to encourage making statistical analysis and the management of the data, a top priority for the business. Businesses are going a step further which makes predictive analytics another trend which is keenly anticipated.
For existing BI professionals or students or professionals looking to switch career tracks with a business intelligence course this is quite an exciting time to be a part of this industry. BI has become an essential practice for all businesses that want to gain a competitive edge in 2020 thereby pushing up the demand for business intelligence and analytics courses. We can conclude this post by saying that it is high time the language of metadata and Big Data became common parlance for industry professionals and aspirants alike.