Top 10 Business Intelligence and Data Visualization Trends


    Data Visualization

    Data VisualizationData exploded and became Big Data, so has Business Intelligence and Data Visualization capabilities.

    A lot has changed with the advent of digital era, cloud access, actionable and insightful data visualizations and data dashboards, data has assumed a new meaning in itself. The rise of self-service analytics has democratized the data product chain. Suddenly advanced analytics are just not restricted to analysts. The influx of big data and the speed at which it is produced has challenged enterprises as well as process improvements.

    Against this backdrop, a key challenge is emerging, call it the innovative use of data and the operationalization of both analytics and data management capabilities. Many companies are already expanding the more data the better approach. The growing usage of sensors & surveillance devices, helps in data expansion capabilities harnessed from IoT devices, and the change seems inevitable. As per IDC estimates, 41.6 billion connected IoT devices will exist that would generate 79.4 zettabytes (ZB) of data by 2025.

    Here are the top 10 Business Intelligence and Data Visualization Trends that will dominate this century-


    Augmented Analytics

    The first trend that we are going to talk about is a combination of Human capabilities with machine intelligence – Augmented Analytics. This is going to drive the analytics space in the years to come. People have started realising the power technology like ML, NLP & AI brings to the table and as per IDC’s Worldwide semi-annual Cognitive and Artificial Intelligence Systems Spending Guide, the world spending on AI systems will double the current spending to climb up to $77.6 billion by 2022.


    Data Quality Management (DQM)

    The analytics trends in data quality grew greatly this past year. The development of business intelligence to analyze and extract value from the countless sources of data that we gather at a high scale, brought alongside a bunch of errors and low-quality reports: the disparity of data sources and data types added some more complexity to the data integration process.

    A survey conducted by the Business Application Research Centre stated the data quality management as the most important trend in 2020. It is not only important to gather as much information possible, but the quality and the context in which data is being used and interpreted serves as the main focus for the future of business intelligence.


    Data Governance

    Managing data is becoming more critical regarding BI tools thanks to the increasing number of data sources and their intricacies. In the present business culture, which is driven by data, the latter more often than not lays out the premises on which they base business choices. If the data is of low quality or inaccurate, the resultant business decisions can bring about disaster for the business. Through data governance, only a particular person will have access to and approach data. This serves to make the data reliable progressively, resulting in better and more accurate business choices.


    Plug N’ Play Analytics Solutions

    It is very natural for organisations to adapt to a pre-loaded analytics solution that caters to the need of one or more departments. Analytics project implementation takes a humongous amount of due diligence in terms of scheduling downtimes of existing systems to forming a cadre to rolling it out in phases. It’s hard to get it right in one go, that’s why companies invest a considerable amount of time while formulating the right analytics strategy.


    Integrated Capabilities

    With businesses, often immediate decisions can be as critical and long-term strategies. In its absence, organizations lack fundamental efficiency. This causes business applications to incorporate analytics abilities and content.

    These embedded analytics are all poised to be a dominant BI pattern in 2020. It will help businesses to operate more intelligently through including data analytics into the existing business framework in the form of ERPs, financial programming, CRMs, and marketing automation.


    Collaborative Business Intelligence

    Today, managers and workers need to interact differently as they face an always-more competitive environment. More and more, we see a new kind of business intelligence rising: the collaborative BI. It is a combination of collaboration tools, including social media and other 2.0 technologies which are developed in a context of enhanced collaboration addressing the new challenges the fast-track business provides, where more analyses are done and reports edited. When talking about collaborative BI, the term “self-service BI” quickly pops up in the sense that those self-service tools do not require an IT team to access, interpret and understand all the data.


    Data-driven Culture

    We have mentioned the importance of data-driven decision making in businesses, but next year, creating a data-driven culture in the whole organization will be one of the top priorities for BI professionals and business managers – one of the trends in data analytics that will certainly be most discussed. Making a decision without relying on data could lead to potential damages that will be hard to recover from, but implementing the data culture across departments can prove to be beneficial across the board: the mentality of employees will change, data will be stored on the cloud where is easily accessible, accurate market segmentation will become a standard, and the costs will significantly decrease.


    Clear & Concise Data Visualisation

    The Business Application Research Centre already highlighted the importance of good data discovery/visualisation. A right analytics dashboard leads to greater adoption due to increased usability and lesser time to insight. Also, it extends the promises of a truly self-service BI tool by eliminating the cumbersome filtering and need of assistance to arrive at the insights for the decision-makers.


    NLP Driven Analytical Queries (Chatbot)

    With the usability and adoption being a big challenge with BI & analytics projects, analytics chatbots that provide the answer to user conversational queries possess great potential in this regard. These bots are machine-learning enabled and with more interactions, it trains itself and continues to learn with every passing interaction and offers better insights with lesser efforts.

    A BI system requires decision-makers to set filters, drill through dashboards and then get actionable information, any step missed could lead to a potentially bad business decision. A chatbot offers a safe and secure remedy for such incidents.


    Mobile BI

    Mobile business intelligence is becoming more incorporated into BI solutions and next year the trend will certainly not lose its importance. In fact, it is one of the most prominent emerging trends in business intelligence identified by almost 3000 professionals in the industry by the research we mentioned at the beginning of the article.

    Mobile BI enables companies to have access to their data also in real-time, ensuring faster reactions to any business occurrences and giving more freedom to users that are currently not in the office but need to access their data.

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