cool hit counter Insight into the 11 trends in business intelligence for 2018 and capturing the secrets to success in the analytics economy!_Intefrankly

Insight into the 11 trends in business intelligence for 2018 and capturing the secrets to success in the analytics economy!

With 2018 already kicked off, are you well prepared to unload the holiday lull and get back into struggle mode to win a head start on success in an analytical economy?

Today, many successful companies have found their way to connect data, people, and ideas. The increasing decentralization of data, computing and usage is an unstoppable force today, and what really sets these businesses apart is how they take advantage of this trend.

This insight-information-driven digital transformation - using data as a strategic asset to make better business decisions - is more prevalent than ever, thus increasing the need for data literacy across the organization. However, adapting to this reality can be fraught with challenges. As information chaos becomes prominent in 2017, the data environment can be difficult to manage, prompting an increase in demand for management, security and data quality.

The question is: how do we maintain a balance between stepping into the analytics economy and protecting privacy? Freeing dispersed data, people and ideas from their silos and connecting them in a flexible, innovative and controlled way - that's "breaking down data silos".

Here are 11 emerging trends in business intelligence for 2018 that will help organizations break down data silos and transform by understanding and reacting to them.

Trend 1: Data literacy will become a priority for business and society

Data literacy is considered to be the ability to read, process, analyze and explore data and has become increasingly important in today's analytics economy. In fact, Gartner1 predicts that "by 2020, 80 percent of organizations will begin to develop deliberate qualities in the area of data literacy, acknowledging the extreme lack of data literacy. "To start making this change, leading software companies will begin offering these types of programs in 2018, and good user organizations will take a structured approach to improving data literacy.

According to a Qlik survey2, nearly 50% of employees struggle to distinguish between data facts and data processing. While less than 20% of employees are considered data literate, those who are claim to be performing well at work (76% compared to 49% who are not data literate). However 65% said they would be willing to invest more time and effort to improve their data skills if given the opportunity.

Trend 2: Hybrid multi-clouds will emerge, connecting the dots

Cloud services will grow faster than even IT leaders can imagine. But in 2018, some data needs to be moved out of the cloud for management, security, cost and performance purposes. In addition to more "edge" computing, this will lead to the emergence of fragmented data and application domains.

This means that analytics architectures that can handle multi-cloud, multi-platform and hybrid environments will become the new standard. Currently, Netskope3 estimates that the average enterprise runs nearly 1,000 different cloud services.

Trend 3: Data goes to the forefront

There are a growing number of use cases, particularly IoT, offline mobility and immersive analytics, where it is more beneficial for organizations to run workloads locally rather than through a public data center. The result is that workloads running directly on a variety of devices will increase significantly in 2018 - as sometimes this approach is better suited to latency, bandwidth, autonomy and privacy.

By 2019, at least 40% of the data created by the IoT will be stored, processed, analyzed and executed near or at the edge of the network. 4 By 2022, 75 percent of enterprise-generated data will be created and processed outside of a traditional centralized data center or cloud due to digital business projects - compared to less than 10 percent today. 5

Trend 4: Big data, data discovery and data science will converge

Often, these three domains are separate from each other, as their users use different tools and skills. While this is still sometimes the case (e.g., data scientists and engineers are supposed to be the ones dealing with algorithms and data models), there are now more ways to share their work with a broader group of audiences.

Promising advances in machine intelligence, big data indexing and engine-to-engine integration are opening up new opportunities for users to fully explore a variety of complex big data sets.

Trend 5: Data Catalogs Will Be the Next Self-Service Frontier

For a person to be truly data literate, it is critical that he or she be able to not only analyze data, but also read, process and explore it. As a result, in recent years, it has become easier to go beyond self-service analysis and do self-service data preparation in a more visually appealing way. In 2017, we saw the same self-service trend in the data directory space. However, these services are still primarily geared towards experts and applied to data lakes.

In 2018, a new approach to data cataloging will more deeply integrate the data preparation and analysis experience. This helps bring it to a broader audience group, enabling them to easily integrate managed enterprise data, data lakes and external data as a service.

Trend 6: APIs in the Spotlight for Interoperability and the Need for New Business Models

Data, computing and usage have become more decentralized, and with it, the enterprise technology landscape. Companies are no longer looking for end-to-end solutions and single stacks because it doesn't fit with their architecture. Instead, look for parts that can be easily connected together, as communication between different software systems is more important.

This means that analytics platforms in this new environment need to be open, interoperable, and have scalable, embedded, and modern APIs. This interoperability will shift analytics from one destination to another, embedding it deeper in the workflow, thus blurring the lines between business intelligence applications as we know them today into data-driven app applications that drive the analytics economy.

Trend 7: Blockchain's rapid growth will drive experimental apps beyond cryptocurrencies

The proliferation of new technologies for processing, managing and integrating dispersed data has allowed the data location to become a diminishing part of the information strategy. This means that blockchain and peer-to-peer technology will inspire all sorts of ideas. While this is still in the beginning stages, 2018 will see innovation move beyond cryptocurrency and into analytics and data management pilot applications.

Initially, connecting blockchain ledgers will bring benefits. Ultimately, however, value may depend on the ability to use blockchain technology to verify data along and authenticity.

Trend 8: Analytics becomes conversational

Traditional analytics use is concerned with drag-and-drop dashboard list boxes and/or visualizations. While there is still value in this, there are now more "conversational analytics" approaches that simplify analysis, findings and narrative, and make it easier for users to reach an important data point.

This may include natural language querying, processing and generation through search and speech enhancement. This technology offers new ways of interaction with the help of virtual assistants and chatbots through API integration.

Trend 9: Redefined reporting, now highly contextualized

We recognise that not everyone will be able to explore their data in detail every time, meaning we will encounter users with different skill levels. This means that in 2018, reporting will begin to be redefined in a way that provides highly contextualized information for analysts and participants - which turns analysis as we know it today on its head.

Instead of traveling to a destination to perform analytics, it is embedded in the user's workspace, bringing the right information to the right person at the right time, in the right place, and in the right context. In the process, there will be more data and analysis available to more people than ever before.

Trend 10: Analytics becomes immersive

Given that virtual reality devices are somewhat too expensive for widespread adoption yet, it will still be a few years before we achieve augmented reality. There may be breakthroughs in enterprise use cases where analytics play an important role. But immersive experiences may also take other forms of user engagement from an emotional social perspective.

Better user interfaces, large screen displays within the digital environment space, better data narratives and collaboration capabilities will attract more people to analytics.

Trend 11: Augmented intelligence systems turn users into participants and facilitators

Because augmented intelligence will be a big part of all the key trends, it is the 11th biggest trend of 2018.

In its current state, the most effective use of artificial intelligence (AI) is to apply it to a diverse but specific set of problems. But in 2018 and beyond, blending AI with technologies such as intelligent agents, bots and automated activities, coupled with traditional analytics tools (such as datasets, visualizations, dashboards and reports) will make data even more useful. But that alone is not enough. And systems where machine intelligence and humans participate in a broader ecosystem and where the two communicate and learn from each other are known as augmented intelligence.

Management, security and data quality are becoming increasingly important in an increasingly challenging environment. But to thrive in the analytics economy, organizations need novel ways to undertake these initiatives while also dealing with an increasingly fragmented environment. Leveraging a truly open platform with an ecosystem that manages the latest trends, technologies and approaches will bring data, people and ideas together. This will give rise to more data-literate users, innovation and enhanced intelligence - thus helping to smoothly integrate data into our lives.

Are you ready to start acting on these new trends?

Qlik can help you with this. With Qlik's innovative information correlation technology, you can break down the silos that exist between data, people and ideas in order to succeed big in the analytics economy. Our platform allows you to bring all your data together and explore it freely from any direction, without missing any data and without revealing paths, using Associative Difference to discover the keys to success.

1Source: Gartner: information as a second language: achieving data literacy for a digital society; February 2017

2 Source: Qlik Data Literacy Survey, September 2017

3 Source: Netskope: Netskope Cloud Report, September 2017

4IDC: FutureScape : World Internet of Things (IoT) 2017 Predictions

5Gartner: data management capabilities are starting to edge out, Ted Friedman, September 2017

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