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Six trends shaping the world of BI

We are halfway through 2016 and technological growth is powering ahead with no signs of slowing down. With such momentum, the question is not whether data development is moving but where the specific growth areas are that will transform the current status quo in the coming year. Even in a time of ongoing upheaval, some factors remained unchanged.

BI and analytics were still the “#1 investment priority for CIOs” in 2015, according to Gartner. Broader use of predictive analytics remains an aspirational goal for most companies. Suboptimal data quality continues to be problematic. The requirement for information governance is high, but maturity is lower than it needs to be. These are a few trends that remained constant in 2015.

Here are the top six trends that we foresee developing within the BI industry as we head further into 2016.

Data consumers are transforming into information activists

Rather than just consuming information, users are now engaging in data prep and profiling. An obvious outcome of this information activism is how people are using visual data discovery to explore not just business data, but topics that interest them personally. As a result, visualisation is now becoming a form of self-expression.

By creating visual apps, users are expressing their views and learning about themselves through being actively engaged with the growing volumes of data. You can see this trend in the rise of the quantified-self movement at an individual level and data-driven journalism in the mass media, altering how people are using public data to understand how society works.

Governed data discovery becomes essential

Self-service BI is the new normal — but that doesn’t mean anarchy. With more data out there, users want to become more self-sufficient in creating their own analyses rather than relying on others, but this means they need to work in a managed data space. As such, governed data discovery is becoming a top priority. Within a framework of governance, users will focus their energy on getting insights from their analyses. They’re able to ask “why?” multiple times, rather than question whether the data is correct. When everyone is using the same information, more efficient, accurate decisions are made.

Big data moves beyond hype to pragmatism

In 2016 we’ll get past the big data hype, as more organisations start to apply some of the long standing practice of data analytics to data sources that used to fall outside of the BI space. Rather than treating new data sources as unfamiliar and novel, data usage is evolving into a richer and complex landscape from various sources, enabling the use of practical, variant data use cases. After all, the maximum decision value is in the nodes where traditional BI data — say, financial transactions — and big data are melded together.

Data from external sources gives better context

Enabling users to see a broad range of factors contributing to their business is becoming more important than ever. With the ability to combine both internal and external data sources, users now have access to more context around their data, which ultimately leads to more insights and better decisions. Adding socio-demographic or location data to analysis easily and quickly can help organizations de-risk some of their management choices.

More data storytelling equals more engagement

People routinely tell stories in work tasks. In fact, when making a proposal to a group, 86 percent almost always or often take time to “lay out what has happened previously,” and 80 percent almost always or often take time to “project forward or to predict possible outcomes.”

Storytelling not only personalises the task at hand, but it can also make it more memorable, impactful, and relevant for those that hear it. In 2016, there will no longer be an excuse to “take that offline.” People will use interactive storytelling to deliver information in a more compelling way that prompts them to take action in the moment, when the insight emerges.

A screen in the hand is worth two on the desk

Mobility is becoming more important than ever for data users. This means that enabling multi-device lensing of BI and analytics will gain importance. Australian smartphone penetration approached 85% by mid-2015, while surveys have shown that about 60% of respondents have a tablet. These overall figures are forecast to rise in 2016 as a greater number of competitively priced units hit the market and as LTE networks increase their coverage.

Having unlimited access to their data can help users ask “why?” any time, and find the answer quickly. BI and visualisation solutions that don’t support users moving from device to device, often and at speed, will not deliver the kinds of experience that people want.

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  1. Information activism, data journalism, the quantified self movement, etc are all signs of how ubiquitous analytics has become. I think that any service, product or even paradigm in analytics must be first successful with the individual data “consumer” before it can be successful with an enterprise. Even the smallest of apps (like ToDo lists, calendars) have started providing data visualizations.

    Another interesting observation from the author is “self service BI is not anarchy”. Standardizing the structure of data is critical to making data discoverable. But this is also tricky, since. first and foremost, enterprises (unless they have an interest in making their data discoverable), would not want to share their schema. Secondly, even if they did so, the problem of data standardization itself is very difficult. This is why we have countless open-data consortiums, but users still have to spend a lot of their time and money beating data into shape. Standardized data ingestion protocols will go a long way in helping with this. (http://nbviewer.jupyter.org/format/slides/github/jaidevd/jaidevd.github.io/blob/source/blog/posts/continuous-integration-for-data-scientists.ipynb)

    Using data from different domains to solve a single problem has come to be seen as a very effective strategy in many applications, especially in crowdsourced data analysis. Most hackathons and Kaggle competitions are won by people who use domain specific knowledge and data for a given problem in addition to using the raw data provided by the organizers.

  2. The Six Trends described above are all related to each other and is centered around only one common thing,that is “HUMAN BEING”.All the above trends which are being set is all based on the data present as well as the data which is being created and how people are using it everywhere else.In order to develop Business Intelligence and to make it a necessary requirement for all the businesses which are present around us,we must make sure the above trends are always set.So to do that it should always be ensured that the data which is being used is authentic and the results which are being derived are also authentic.Data governance should be maintained and also new sources of data which are being created everyday and every moment should be scrutinized for further usage.
    The demand of data has increased so much that the population of data literates have increased exponentially which has also made the data mobility increase.Measures should be taken such that the availability of data is always on the go,and apps should be developed so that even on the go data consumers can make deductions on the basis of data and can be ready with their work always.Data Usage Tools should be available to the user such that the tools are present in the conditions of their usability.

  3. Governance of data would require investment and hence returns would be expected. So data monetization will receive a good boost and it won’t be a surprise in the near future when we would be able to see firms maintaining digital data. Also there still exists a large source of written and documented data which still needs to be digitized so as to gain insights. So opportunities are always there.
    We use a lot of apps today which helps in building insights which were completely unavailable a few years back but today even a simple google search, twitter tweet or any facebook post or even the new emojis helps in generating insights and knowing the sentiment of the society. How interesting could it get when such sentiment data is combined with entertainment industry and product launches take place when the “society sentiment” is apt or suitable for it. This is just one example but there will be many more!!

  4. In this digital era where anyone can upload wrong information/data and confuse the customers the need for governed data becomes essential. Providing the source and the methodology behind acquiring data makes it more reliable for the customers to trust the facts and also the firms who try to predict the future market trends based on this data.
    Expressing your results with Visual data adds another dimension to your storytelling. It helps the readers understand the stats and trends better and quicker. It will also attract more viewers as Visual data needs less attention spans than those long boring blog posts, which are highly likely to be skipped by most of the users these days.
    Another crucial insight this article brings is the shift from traditional PCs and laptops to mobiles. And this will continue to rise as the post suggests. The mobile platform essentially lacks in the data storage and security aspects. It’ll be wonderful if data could be stored on the cloud and not on users mobile. This will reduce the space consumption on the users mobile and can also solve the security issue as the data will now be managed by the professional cloud companies.

  5. Integration of BI application with Graphics is great approach to understand essence of context of the data.
    using visual representation of data provides ease of access and also looks more attractive.

  6. Its very true ,Business intelligence is new normal in shaping enterprise initiatives and helping ventures to provide quality services.
    Fast growing network of embedded devices or IoT is emerging as storm yielding massive data for governed data and analytics. But what i think the serious challenge is to integrate these data and profiling it discreetly for individual e.g now every user has multiple screen like smartphone,tablet,laptop,PC etc and multi-screen mobility will keep affecting dashboard and business intelligence application design and development.so developers must think in direction of integrating data when developing new BI application

  7. I completely agree with the article about to manage and do the anlaysis of the generated data but I seriously think the need of the hour is data security. Data is getting generated at a very pace, Startups are increasing at a very fast. These startups are having data about millions of users and many of these startups sites and apps lack in security. So, everyone should work keeping the security management of data in mind.

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