BI software maker Tableau presents top 10 BI trends for the new year
Don’t fear AI
Machine learning can make the data analytics process more efficient, leaving the analysts with more time to think about business implications and the next logical steps. It also helps the analyst explore and stay in the flow of their data analysis because they no longer have to stop and crunch the numbers. Instead, the analyst is asking the next question.
The human impact of liberal arts
As analytics evolves to be more art and less science, the focus has shifted from simply delivering the data to crafting data-driven stories that inevitably lead to decisions.
The promise of NLP
The rising popularity of Amazon Alexa, Google Home, and Microsoft Cortana have nurtured people’s expectations that they can speak to their software and it will understand what to do. This same concept is also being applied to data, making it easier for everyone to ask questions and analyze the data they have at hand.
The debate for multi-cloud rages on
As multi-cloud adoption rises, organizations will have to manoeuvre through the nuance of assessing whether their strategy measures how much of each cloud platform was adopted, internal usage, and the workload demands and implementation costs.
Rise of the Chief Data Officer
To derive actionable insights from data through analytics investments, organizations are increasingly realizing the need for accountability in the C-Suite to create a culture of analytics. For a growing number of organizations, 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 of the organization. This allows the CIO to have a more strategic focus on things such as data security.
The Future of Data Governance is Crowdsourced
BI and analytics strategies will embrace the modern governance model: IT departments and data engineers will curate and prepare trusted data sources, and as self-service is mainstreamed, end users will have the freedom to explore data that is trusted and secure. Top-down processes that only address IT control will be discarded in favor of a collaborative development process combining the talents of IT and end users.
Vulnerability Leads to a Rise in Data Insurance
Cyber and privacy insurance covers a business’ liability for a data breach in which the customer’s personal information is exposed or stolen by a hacker. Data’s As data’s value increases and so do the threats, companies will look for an option Z—the last option.
Increased prominence of the data engineer role
Data engineers are responsible for extracting data from the foundational systems of the business in a way that can be used and leveraged to make insights and decisions. As the rate of data and storage capacity increases, someone with deep technical knowledge of the different systems, architecture, and the ability to understand what the business wants or needs starts to become ever more crucial.
The location of things will drive IoT innovation
One positive trend that is being seen is the usage and benefits of leveraging location-based data with IoT devices. This subcategory, termed “location of things,” provides IoT devices with sensing and communicates their geographic position. By knowing where an IoT device is located, it allows us to add context, better understand what is happening and what we predict will happen in a specific location.
As it relates to analyzing the data, location-based figures can be viewed as an input versus an output of results. If the data is available, analysts can incorporate this information with their analysis to better understand what is happening, where it is happening, and what they should expect to happen in a contextual area.
Universities double down on data science and analytics programs
The hard skills of analytics are no longer an elective; they are a mandate. 2018 will begin to see a more rigorous approach to making sure students possess the skills to join the modern workforce. And as companies continue to refine their data to extract the most value, the demand for a highly data-savvy workforce will exist — and grow.