DEFINITION: Business Intelligence Top Trends
The pace and evolution of business intelligence solutions mean what’s working now may need refining tomorrow. From natural language processing to the rise in data insurance, we interviewed customers and Tableau staff to identify the 10 impactful trends you will be talking about in 2018. Whether you’re a data rockstar or an IT hero or an executive building your BI empire, these trends emphasize strategic priorities that could help take your organization to the next level.
“Machine Learning helps you look under tons of rocks when you need assistance getting an answer”
Tableau & Gartner.com, Discuss ‘Top 10 Business Intelligence Trends’
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How Machine Learning Will Enhance the Analyst
Popular culture is fueling a dystopian view of what machine learning can do. But while research and technology continue to improve, machine learning is rapidly becoming a valuable supplement for the analyst. In fact, machine learning is the ultimate assistant to the analyst. Learn more
The Human Impact of Liberal Arts in the Analytics Industry
The analytics industry continues to seek skilled data workers, & organizations look to elevate their analytics team, we may have had a plethora of talent at work all along. We are familiar with how art and storytelling has helped influence the data analytics industry. That doesn’t come as a surprise. What comes as a surprise is how the technical aspects of creating an analytical dashboard, previously reserved for IT and power users, is being taken over by users who understand the art of storytelling—a skill set primarily coming from the liberal arts.
Furthermore, organizations are placing a higher value on hiring workers who can use data and insights to affect change and drive transformation through art & persuasion, not only on the analytics itself. Learn more
The Promise of Natural Language Processing
2018 will see natural language processing (NLP) grow in prevalence, sophistication, and ubiquity. As developers and engineers continue to refine their understanding of NLP, the integration of it into unrealized areas will also grow. 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. For example, by stating a command, This same ‘on demand’ concept is also being applied to data, making it easier for everyone to ask questions and analyze the data they have at hand.
Gartner predicts by 2020 that 50% of analytical queries will be generated via search, NLP or voice. Suddenly it will be much easier for the CEO on the go to quickly ask his mobile device to tell him: “Total sales by customers who purchased staples in New York,” then filter to “orders in the last 30 days,” and then group by “project owner’s department.” Or, your child’s school principal could ask: “What was the average score of students this year,” then filter to “students in 8th grade,” and group by “teacher’s subject.” NLP will empower people to ask more nuanced questions of data and receive relevant answers that lead to better everyday insights and decisions. Learn more
The Debate for Multi-Cloud Rages On
If your organization is exploring and evaluating a multi-cloud strategy in 2018, you’re not alone. “There’s a stampede of organizations moving their data to the cloud and moving their core applications,” said Chief Product Officer Francois Ajenstat. “And whether it’s a ‘lift and shift’ or a re-platforming, we see customers adopting the cloud at a much faster rate than ever.”
According to a recent Gartner study, “a multi-cloud strategy will become the common strategy for 70 percent of enterprises by 2019, up from less than 10 percent today.” Customers are growing sensitive about being locked into a single legacy software solution that doesn’t match their future needs. However, switch and migrations have become relatively easier with similar APIs and the use of open standards like Linux, Postgres, MySQL, and others. Learn more
Rise of the Chief Data Officer
Data and analytics are becoming core to every organization. That is undebatable. As organizations evolve, they’re prioritizing a new level of strategic focus and accountability regarding their analytics.
Historically, most business intelligence efforts were assigned to the Chief Information Officer (CIO), who oversaw standardizing, consolidating, and governing data assets across the organization, which needed consistent reporting. This put BI initiatives (data governance, building analytical models, etc.) in competition with other strategic initiatives (such as IT architecture, system security, or network strategy) under the purview of the CIO—and often inhibited the success and impact of BI. Learn more
The Future of Data Governance is Crowdsourced
The modern business intelligence outfit has progressed from data and content lockdowns to the empowerment of business users everywhere to use trusted, governed data for insights. And as people are learning to use data in more situations, their input on better governance models has become a monumental force within organizations.
It’s an understatement to say that self-service analytics has disrupted the world of business intelligence. The paradigm shifted to anyone having the capacity to create analytics leading to the asking and answering of critical questions across the organization. The same disruption is happening with governance. As self-service analytics expands, a funnel of valuable perspectives and information begins to inspire new and innovative ways to implement governance. Learn more
Vulnerability Leads to a Rise in Data Insurance
For many companies, data is a critical business asset. But how do you measure the value of that data? And what happens when that data is lost or stolen? As we have seen with recent high profile data breaches, a threat to a company’s data can be crippling and potentially cause irreparable damage to the brand.
According to a 2017 study by the Ponemon Institute, the average total cost of a data breach was estimated at $3.62 million. But are companies doing everything they can to protect and insure their data? One industry rapidly growing in response to data breaches is the cybersecurity insurance market. This industry has seen 30 percent year-over-year growth, with the industry set to reach $5.6 billion in annual gross written premium by 2020. Learn more
Increased Prominence of the Data Engineer Role
Here is a certainty: you can’t create a dashboard without having all of your charts built out so you can understand the story you’re trying to communicate. Another principle you likely know: you can’t have a reliable data source without first understanding the type of data that goes into a system and how to get it out.
Data engineers will continue to be an integral part of an organization’s movement to use data to make better decisions about their business. Between 2013 and 2015, the number of data engineers more than doubled. And as of October 2017, there were over 2,500 open positions with “data engineer” in the title on LinkedIn, indicating the growing and continued demand for this specialty. Learn more
The Location of Things will Drive IoT Innovation
It’s an understatement to say that the proliferation of the internet of things (IoT) has driven monumental growth in the number of connected devices we see in the world. All of these devices interact with each and capture data that is making a more connected experience. In fact, Gartner predicts that by 2020 the number of IoT devices available to consumers will more than double “with 20.4 billion IoT devices online.”
Despite growth, cases & implementation of IoT data hasn’t followed the same desirable path. Companies have concerns about security, but most don’t have the right organizational skill sets or the internal technical infrastructure with other applications and platforms to support IoT data. Learn more
Universities Double Down on Data Science & Analytics Programs
NC State University is home to the first Master of Science Analytics program. The MSA is housed within their Institute of Advanced Analytics, a data hub with the mission to “produce the world’s finest analytics practitioners—individuals who have mastered complex methods and tools for large-scale data modeling [and] who have a passion for solving challenging problems” As the first of its type, NC State’s program has foreshadowed academia’s pronounced investment in data science & analytics curriculum.
Earlier this year, the University of Cal, San Diego launched a first for their institution—an undergraduate major & minor in data science. They didn’t stop there. The university also made plans, supercharged by an alumnus donation, to create a data science institute. Following suit, UC Berkeley, UC Davis, and UC Santa Cruz have all increased their data science and analytics options for students, with demand exceeding expectations. But why? Learn more
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