In 1995, the World Wide Web was an ecosystem accessed by 16 million users. A little above two decades later, the number is more than 3.5 billion (the world will need more than five computers, right Thomas Watson?!). It’s not rocket science; you don’t need that smart physicist in “Transformers 5” to figure this out (though he was wrong in the end!), to understand that the volume and variety of data being generated every day is massive and unprecedented.
IoT, being viewed as a wave as big as the Industrial Revolution, is about tapping data from sensors, Internet, server logs, and machines, and creating a connected ecosystem comprising a plenitude of devices other than mobile phones and laptops. No wonder, then, that data analytics and business intelligence are back to being the buzzwords in technospheres.
Democratization of data is another significant and evident force in play, with SMBs (small and medium-sized businesses) and enterprises moving many more applications on the cloud, and endorsing modern BI (business intelligence) tools. That said, let’s take you through business intelligence trends and hot technologies in the data analytics space that are already shaping the present and future.
Emergence of connected service platforms and applications
Here are a couple of stats.
- By the end of 2017, tablets and smartphones will comprise 87 percent of the global connected device market.
- By 2020, 74 percent of cloud workloads will be Software as a Service (SaaS).
These, and similar stats, outline the emergence of forces of mobility and cloud connectivity of applications.
On the whole, business intelligence trends point to the emergence of powerful and highly integrated end-to-end IT ecosystems comprising mobile devices, cloud, analytics, and embedded designs. In the consumer segment, we see contemporary sources of data coming to full force, such as mobile apps, social media platforms, online marketplaces, and video streaming services. In enterprises, 24/7 monitoring devices, AI systems, machine-to-machine connectivity, and IoT are the main contributors of workloads and data. As long as they remain out of the hands of Quintessa from “Transformers 5” we should be good to go!
The confluence of all these forces is a highly data-driven ecosystem of processes, tools, businesses, and enterprises. We are witnessing connected supply chains and smart manufacturing in action already, giving shape to a new industrial economy that has data as its strongest pillar.
For BI and analytics, all this is helping create industry standards, standard operating procedures, and best practices. BI and analytics platforms that are keeping in sync with these core forces will continue to be relevant for enterprises looking to invest more in these technologies.
Business intelligence trends: Self-service is the future
Over the past few years, there has been a gradual movement from IT-led reporting to self-service analytics capabilities. This transformation has picked up speed, and is a major positive we see in business intelligence trends and the data analytics space. Business users are highly empowered by self-service BI tools.
These cloud-hosted BI tools help users drive simple, actionable, agile, and relevant decision making without involving IT in the analytics and BI on an operational level. Modern BI and analytics tools have overcome the limitations of traditional data warehousing paradigms and don’t need semantic models to operate.
Offering highly interactive, intuitive, and visual exploration-based experiences, these BI tools deliver massive empowerment to end users. The near future will see more investment in cloud empowered and robust BI platforms with strong capabilities around storage, visualization, qualitative, and statistical analyses, and integration.
BI’s impact via AI technologies
A National Business Research Institute report found that 38 percent of the surveyed enterprises had already adopted AI. AI, of course, is the umbrella term for several technologies such as deep learning, machine learning, predictive analysis, and prescriptive analysis. The report suggested that the number would rise to 68 percent by 2018. The phase of hype is almost over, this is not a fad or a weak trend: We’re witnessing increasing AI adoption in business applications.
As a result, enterprises have also embraced text analytics, natural language generation (NLG), natural language processing (NLP), speech recognition, machine learning, virtual agents, and deep learning platforms.
Thus, the number of sources of raw material for business intelligence and data analytics engines of enterprises is huge. As data variety, velocity, and volumes surge ahead, technologies of data analytics and business intelligence can help enterprises create economic impact by creating better algorithmic models.
Collaborative analytics to the fore
The days of sharing PDFs and PowerPoint slides are waning in large enterprises as more and more employees get connected to the hub of self-service BI and analytics. This wave of collaborative analytics is focused on leveraging on data governance and multidirectional information flows to enable people to share interactive and data-driven information points in real time. BI tools and analytics platforms that can handle the needs and expectations of such kinds of collaborative analytics will find increasing enterprise adoption.
Self-service is extending to data prep
We talked about self-service BI earlier. In a similar way, data prep activities are also on track to be doable by routine end users. Common data prep tasks such as HTML and JSON imports, data parsing, and data wrangling will not require IT service desk tickets, as end users will be able to use transformed interfaces to manage these on their own.
Human-data engagement in more natural ways
The human-data interface is transforming in exciting ways. A part of this change is the shift towards “natural,” as BI technology makers push the envelope to enable natural language processing in their products.
Improvement in natural language processing and generation of results will drive increasing adoption by end users. There is a lot of healthy skepticism around this development. Albeit the potential it offers in terms of enabling people to interact with data using natural language and text makes this trend the most watched.
Potential and promise
We thought it was big when enterprises started moving their analytic capabilities to where their data already was in the cloud.
However, these are much more exciting times, as the business intelligence trends point to promising developments that have tremendous business potential. Right from the confluence of several parallel forces like AI and IoT, to the vendor side of R&D in BI and analytics tools – there’s a lot of potential and promise for data-driven enterprises. It is a brave new world!
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