Over the years, more technological solutions have become available for businesses and other organizations. The development of available technologies has led feats that are achievable in 2019 as well as the available BI tools.
2019 could thus be described as a year when a lot of growth has been achieved in the analytics and BI sector. We cover some of the BI and analytics trends of 2019.
Trends established in the BI and analytics space in 2019, where a buildup of progress achieved in past periods. Thus, we begin by highlighting some of the trends that were established in 2018.
Analytics and BI trends established in 2018
It is noteworthy that, in 2018, cloud storage solutions became readily available. The widespread availability of cloud storage solutions was behind the trends in BI and analytics established in 2018.
One of the trends established in 2018 is available of Analytics that were driven by IoT, and the widespread application of such tools in different sectors. It is noteworthy that IoT pipelines also drove the application of analytics in businesses.
Other trends established in analytics and business intelligence in 2018 include the incorporation of data visualization and self-service options into BI tools. These tools thus improved the efficiency of operations across organizations.
In 2018, Advanced Analytics was also increasingly applied across organizations, serving as a bedrockfor the trends that were developed in 2019.
Analytics trends in 2019
Certain trends, which include the following, have been known to shape activities that are related to analytical techniques.
The embedded analytics trend that has been seen in 2019 has been a distinctive feature between regular operations and intelligent operations of analytical tools. Embedded analytics has allowed organizations to incorporate tools that run intelligent routine activities into their operations. The increasing application of embedded analytics is a trend that has improved the application of analytics in organizations.
An important trend that as regards the application of analytics in businesses is the application of machine learning. The application of machine learning is behind the enhanced ease of accessing a large volume of data by organizations.
It is noteworthy that the application of machine learning is also behind the creation of intuitive interfaces. These intuitive interfaces are known to provide required data in the shortest time. Augmented analytics platforms were also created based on the application of machine learning in analytics.
Improved User Experience
Advancement in analytics technology has led to the improved user experience, an impressive analytics trend of 2019. The improved user experience associated with analytics technology is associated with the availability of forms of technology such as text and speech technology that allows users to make requests using everyday languages.
The incorporation of AI is also behind the improved user experience of analytical tools which has been a notable trend of 2019. In 2019, more chatbots and personal assistants have also been used as analytical tools, contributing to the improved user experience.
Organizations have been able to incorporate a variety of analytical tools into their dashboards, and these tools have ensured the smooth running of operations within these organizations. The improved user experience that has been associated with applications of analytics in 2019 has encouraged the adoption of analytical tools in more species.
Cloud analytics has improved significantly as a notable trend of 2019. Cloud analytics is critical to the expanded application of analytical solutions indifferent. The improved adoption of cloud storage solutions trend which developed in 2018 has even improved in 2019 as more organizations as adopting cloud storage either as the total form of storage or as part of incorporated storage tools.
Businesses, especially small businesses, are adopting cloud analytics because of the obvious benefits such as reduced cost and expended value. The accessibility and ease of use of cloud storage is another reason behind the significant improvement in its adoption. For certain organizations, cloud storage is a major form of data storage. In other organizations, data that cannot be stored on the cloud are stored within on-site facilities. Such organizations apply a hybrid storage system that combines on-site storage with cloud storage.
The significantly increasing use of cloud storage in organizations is driven by the fact every organization seeks cost-effective ways of running their operations and cloud analytics have fulfilled this purpose excellently.
2019 has seen a lot of technology becoming available for analytics and similar operations. However, the availability of technology does not exactly solve all the problems organizations will encounter as regards analytical option.
The lack of appropriate analytics skills and culture is thus a continuing trend of 2019, one that, sadly, can’t be fixed with technology. This trend reflects the need for organizations to invest in the development of analytical skills as well as an analytical culture.
An analytical trend of 2019 is thus the fact that data literacy is still an issue that organizations should tackle.
The insight gotten from analytical tools is meant to be actionable. In the past, a lot of investments have not been made on end-to-end approaches of converting insights into actionable information. 2019 is experiencing a different trend, a welcome trend.
Although the application of insights gotten from analytical tools largely depends on professionals and executives within organizations, integrative technology encourages the conversion of insights into actionable results.
2019 has seen more focus on end-to-end approaches of getting actual results from analytics. Actions in this direction include the development and adoption of more social collaboration platforms. Attention has also been placed on developing platforms that encourage collaborative planning activities.
An interesting analytical trend of 2019 is the evolution of analytics from traditional analytics to the newer form of analytics. Traditional analytics has been helpful but had its limitations, which included the restricted incorporation of structured data.
The new analytics experience allows the seamless integration of both structured and unstructured data towards the best consumer experience. The new analytics experience that is seen in 2019 and beyond is more fluid and actionable. This new experience is also built for actionable results.
A lot can be achieved with AI, and developers are exploring the technology in different forms trying to make the most of it and integrate it into existing platforms. The task of striving to make the most of AI is bound to unearth numerous challenges as regards the use of AI.
As AI is being explored, existing challenges will be amplified. These challenges include the data bias challenge and the data quality challenge. The exploration of applications and possibilities with AI will also amplify the existing ethics and privacy challenges.
The application of AI is bound to accompanied with numerous challenges such as those highlighted above, as a trend of 2019. There is thus a call for more effective regulations and policies in that regard. As organizations apply developing technologies, there are bound to be challenged. Organizations are thus tasked with effecting measures to ensure that these challenges do not lead to full-blown disasters.
The challenges that are bound to accompany the application of AI are to be managed by both governments and organizations.
Over time, research and experiences have highlighted the fact that analytics is most effective when human qualities are reflected. These human qualities include creativity and leadership. To ensure the effectiveness of analytics, analytics is being made more human incorporating the essential qualities.
Analytics drives solutions that are made across the different sectors where the different analytical tools are applied. For these decisions to achieve the most effect, they must incorporate essential human qualities, and this is a trend that is driving activities as regards analytics in 2019.
Data Management Compliance
Even with the strides that have been achieved as regards data collection and analysis, the issue of compliance is still prevalent. The issues that have plagued data management also include privacy concerns.
The issues that plague data management have inspired the activities of the major players in the analytics space. These issues are driving the application of standardized approaches in data collection and analysis, as well as every other process involved in data management. Approaches that have been applied include those that reduce the attractiveness of data as it is collected and processed.
In adopting more effective approaches in managing the issues that have been associated with data collection and analysis include the development of new systems for orchestrating data. Real-time data processing platforms have also been developed as a way of managing the challenges associated with data management with analytical tools.
Overall, the analytics trend of 2019 is an indication of the growth that has been achieved as well as the struggles. The trends indicate the willingness of the players in the sector to maximize the available opportunities.
In line with striving towards the most efficient application of available technology, specific BI solutions have been introduced in 2019. These BI solutions, in addition to the old, are built to improve user experience and ensure better incorporation of available technologies into the operations of organizations across the different sectors.
Some of the BI solutions that have been introduced as well as those that are bound to be introduced are highlighted below. Trends that have established in 2019 as regards BI are highlighted below.
Self-service analytics: Self-service analytics is increasingly driving a lot of BI activities. There have been predictions that there will be more collaboration between self-service analytics and users of BI than BI users and data scientists. This prediction has been evident in 2019. The shift towards self-service analytics could be attributed to the fact that organizations are constantly seeking ways to improve consumer experience and carry out operations efficiently, which are achievable with self-service tools.
Chief data officer: In ensuring better coordination of BI activities, more organizations are appointing chief data officers that are saddled with responsibilities such as implementing proper data governance guidelines. The duties of chief data officers in the organization also include creating an analytical culture.
Data discovery: Although BI tools already serve the purpose of data analysis properly, the restricted nature of these tools in periods of rushed decision making remains an issue. This issue is being addressed with the availability of advanced data discovery tools, a notable trend in the BI space. Typically, executives work with data scientists during periods when urgent decision making is necessary. The availability of advanced data discovery tools is bound to be associated with reduced reliance on data scientists as well as guarantee the timely operations of executives.
Trends that apply to analytics also apply to BI. These trends include the enhanced adoption of cloud technology as more organizations are moving sections of the activities, as deemed appropriate to clouds. In a bid to make BI tools more relatable to the average, augmented BI is a trend that is especially notable in 2019. Data quality is also a focus of BI as tools for managing a unified database instead of numerous databases have been developed in 2019.
A lot of the trends of 2019 as regards BI and analytics are trends that both spheres have been working at for long periods. These trends are also an indication of possible future trends. In 2020 and beyond, tools and measures that push analytics forward are expected. It is also expected that stricter regulations will be implemented in managing the challenges that are currently experienced in 2019.
More organizations are adopting analytics tools and acknowledging the possibilities of BI. Thus, it is expected that organizations, in general, will pay better attention to the available technology. Budgets of organizations for BI, for example, are expected to expand.
Although cloud technology is already in use and has been welcomed across organizations, in the future, the capabilities of cloud technology are bound to improve broaden. Through this evolution, the technology will also remain quite affordable for different organizations. Experts have also predicted that, in the future, deep learning may overshadow machine learning towards providing the necessary insights. These insights are expected to be provided based on intuitive operations of analytical tools.