Data is invaluable to all companies, from budding startups to global enterprises.
This growing commodity is triggering organizations to deploy BI solutions that will elevate and accelerate data-driven decisions.
Successful organizations are prioritizing a modern BI approach, and in turn, priming their workforce to be the most analytically savvy generation ever seen.
For a competitive edge in 2018, organizations must recognize the strategies, technologies, and business roles that can enhance their approach to business intelligence.
Here are some of the most critical trends to bear in mind looking ahead to a new year, and even beyond.
Don’t Fear AI: How machine learning will enhance the analyst
Popular culture is fueling a dystopian view of what artificial intelligence can do.
But while research and technology continue to improve, machine learning is rapidly becoming a valuable supplement for the analyst, providing assistance and driving efficiency.
By automating simple, yet labor-intensive tasks like basic math, analysts gain time to think strategically about the business implications of their analysis and plan for next steps.
Secondly, it helps the analyst stay in the flow of their data. Without stopping to crunch numbers, analysts can ask the next questions to drill deeper.
Machine learning’s potential to aid an analyst is undeniable, but it’s critical to recognize that it should be embraced when there are clearly defined outcomes.
While there might be concern over being replaced, machine learning will supercharge analysts and make them more precise and impactful to the business.
The Promise of Natural Language Processing (NLP)
Gartner predicts that by 2020, 50 percent of analytical queries will be generated via search, natural language processing (NLP), or voice.
NLP will empower people to ask more nuanced questions of data and receive relevant answers that lead to better insights and decisions.
Simultaneously, developers and engineers will make greater strides in exploring how people use NLP by examining how people ask questions – from instant gratification to exploration.
The biggest analytic gains will come from tackling this ambiguity and understanding the diverse workflows that NLP augments.
The opportunity will arise not from placing NLP in every situation, but making it available in the right workflows so it becomes second nature to those using it.
The Future of Data Governance is Crowdsourced
It’s an understatement to say self-service analytics has disrupted business intelligence, and the same disruption is happening with governance.
As self-service analytics expands, a funnel of valuable perspectives and information inspires new and innovative ways to implement governance.
Governance is as much about using the wisdom of the crowd to get the right data to the right person as it is locking down data from the wrong person.
BI and analytics strategies will embrace the modern governance model in 2018: IT departments and data engineers will curate and prepare trusted data sources, and with self-service going mainstream, end users will be free to explore trusted, secure data.
The Debate for Multi-Cloud Rages On
According to Gartner, “a multi-cloud strategy will become the common strategy for 70 percent of enterprises by 2019.”
As enterprises grow increasingly wary about being tied to a single legacy solution, evaluating and implementing a multi-cloud environment can determine who provides the best performance and support for each situation.
However, while flexibility is a plus, this approach increases overhead cost by splitting workloads across providers and forcing internal developers to learn multiple platforms.
With multi-cloud adoption on the rise, organizations must assess their strategy and measure adoption, internal usage, workload demands and implementation costs for each platform.
Rise of the Chief Data Officer
Data and analytics are becoming core to every organization. But in some cases, a gap forms between a CIO and the business while battling security and governance versus speed to insight.
With that, the C-Suite is becoming more accountable for creating a culture of analytics.
For many, the answer is appointing a Chief Data Officer (CDO) or Chief Analytics Officer (CAO) to lead business process change, overcome cultural barriers, and communicate the value of analytics at all levels.
The role of the CDO/CAO is outcome-focused and they ensure there are proactive C-level conversations happening about how to develop an analytics strategy from the get-go.
This article was published in partnership with Tableau Software.