Trends business intelligence software

Time and again, we have mentioned how important data can be to an organization. The benefits of having accurate, understandable, and complete data transcend better decision-making. All that said, leaving data unattended can dilute all these benefits and leave you counting losses.

Just look around, companies like TMobile, Facebook, and MyHeritage suffered shocking data security breaches in The cyberattacks dragged these companies through mud and left millions of their users exposed. In the modern era, there are millions of cyberattackers sniffing for an opportunity to strike.

The worst is that they attack all types of businesses, big and small. There is always a chance of successful attacks for companies that have not implemented impervious security layers.

The rampant cases of cybersecurity breaches underpin the importance of data security. Data security trend picked up speed in , and we predict that in , businesses will continue to search for more secure solutions. Consumers are now fully aware of the value of personal information and are skeptical about sharing it online. In a bid to instill trust and collect the data they need, companies will continue to mend all loopholes for security breaches. Like data governance, security is one of the hottest business intelligence trends in healthcare and financial services.

Artificial intelligence AI has taken every business aspect by storm, and business intelligence is no exception. The outsized potential of this technology, promises to augment human intelligence by revolutionizing the way we interact with business data and analytics. The answer is a big NO! However, there is a consensus that AI can process vast quantities of data faster than humans.

Besides, the technology offers a unique perspective in business intelligence and makes it easy to unearth insights that have gone previously unnoticed. Furthermore, the ability to clarify the relevance of bits of information on a granular level and understand how data metamorphoses into real business decisions seem too attractive to forego. As a result, organizations are in a rush to embrace the confluence of AI and BI in business. No one wants to play catchup later. Of course, there are risks involved, and businesses are well aware of this fact.

Explainable AI is an exercise of understanding and presenting clear-cut views into machine learning systems. We expect more critical developments to emerge in the coming year s. All that said, we do not see the AI trend in BI going anywhere: its disruptive impact will be felt beyond These days, data is the livelihood of any business.

Data helps a company predict customer expectations, obtain competitor information, execute effective product management, and make informed top-down decisions.

There is no doubt big data has a tremendous impact on the trajectory of any business. However, there is one critical caveat — if the data is not accurate, up-to-date, consistent, and complete, it can destroy business value and deplete profitability. Poor data quality is a problem that has long plagued enterprises of all sizes. Consequently, the problem is poised to worsen as data sources increasingly become interwoven. Data quality management is an integral process that combines technology, process, the right people, and organizational culture to deliver data that is not only accurate but also useful.

More importantly, data quality is not about being good or bad; its a range of metrics that measure the health of data used for analysis. Data quality management DQM provides insights into data pumping through a business. It improves the data governance framework and enforces data standardization, ensuring that data used for analysis can provide a clear picture of the day-to-day business operations. As a result, business leaders can make accurate decisions that drive the business forward.

Today, every business wants to implement data quality processes to enhance its ability to utilize business intelligence. Going by the significance it has gained, this trend is set to continue to cause ripples in Actionable analytics is one of the hottest analytics and business intelligence trends in and it is bound to continue in and beyond. Traditionally, business intelligence data and insights were not consumed in the same place. However, in a bid to stay on top of business workflows and processes, businesses are no longer interested in analyzing data in one silo and taking action in another.

Luckily, modern BI tools have evolved to put corporate data where users want to take action. The platforms are merging with critical business processes and workflow through features like embedded analytics, dashboard extensions, and APIs. What happens is that with these capabilities, business users can work on data, derive actionable insights, and implement them all in one place. Additionally, modern BI tools feature mobile analytics to deliver unique capabilities where the user is.

Moreover, putting actionable analytics in context helps customize insights to the specific department, business, or industry. Even though this is one of the emerging trends in business intelligence, its popularity is already widespread. Already, several frontrunners are trailblazing the way for this trend. For example, Looker is one of the most well-known embedded analytics software driving the trend forward.

On the other hand, Sisense has plans to invent new analytics delivery models. Lastly, SharePoint is providing internal portals to enable organizations to embed analytics. Since , data discovery has been one of the most important business intelligence trends. Data discovery is a business user-centric process of collecting data from multiple silos and databases and assembling them into a unified source to simplify analysis.

So, why is data discovery important? However, even with the vast amount of data, many are unable to draw actual value from every bit of information. This is because of the mismatch that exists between people who prepare corporate information for analysis and people who perform the analysis and consume the insights. Interestingly, data discovery systems help businesses get around this problem. It makes it easy for people with no IT skills to access and drill down into data to derive the information they need.

This way, non-tech users can explore corporate information and obtain actionable insights to make fast, informed decisions based on their discoveries. Using robust data visualization tools makes this process intuitive, fun, and fast. Data visualization is way better than the usual static reports. Data visualization has advanced to include heat maps, pivot-tables, and geographical maps.

As a result, businesses can now create high-fidelity presentations of their discoveries. The data discovery trend is poised to persist as one of the most critical business intelligence trends in the coming years. There you have it, our compilation of the hottest business intelligence trends that will shape the industry in and beyond. Thankfully, with these trends, we have an inkling of the exciting things to expect in the coming years.

Currently, there is overwhelming pressure for industry players to implement strategies like storytelling, data discovery, data quality management, and collaborative BI.

Robots will continue to focus on repetitive tasks but will do things smarter. The evolving technology framework built on the Internet of Things, AI and analytics allows companies to process business intelligence with greater clarity, depth, and precision. Thus, manufacturing is being pushed towards collaborative production, real-time decision-making, predictive and remote maintenance, and simulation and optimization Statista, In the meantime, humans will find themselves doing higher-level tasks such as strategy, management, and design.

Data-driven decisions are only as good as data integrity, which makes data quality management a critical focus of business intelligence software trends. We are seeing data warehouse modernization scale exponentially in the coming years to meet the unstoppable onslaught of big data. Pundits put the total date center IP traffic at To meet the challenge head-on, BI vendors along with the broader analytics industry will continue to advance their warehousing tools and systems, as businesses pay close attention to the right platform for their needs and data infrastructure.

We shall see further integration of machine learning algorithms in BI processes. AI-powered features will be put to task to manage exhausting warehousing processes, mainly for descriptive analytics and predictive analytics.

Tasks such as parsing historical data, data benchmarking, forecast modeling, and simulation of numerous scenarios will be handed over entirely to machine learning. Meanwhile, humans will focus on tasks that require context, creativity, and collaboration, mainly the processes in diagnostic analytics and prescriptive analytics. The future of data centers sits solid-strong in the realm of hyperscale operators, Google, Amazon, Microsoft, and IBM. Outside of governments, only the tech giants have the financial strength to build industry-scale cloud infrastructure.

Between and , Google, Amazon, and Microsoft have not let up in big-ticket cloud developments. These business intelligence software trends and beyond will propel your business forward with more efficient operations, deeper market insights, and, eventually, more profits. But only those who are prepared for a data-driven future will reap the fruits of the next wave of BI trends. This means, your business intelligence is placed on employees with defined roles and responsibilities and data literacy among employees is imposed to make them aware of the devastating effects of improper data handling.

Additionally, a quality assurance workflow is ready to ensure stringent data governance and, in general, the business assumes a holistic view of the entire data pipeline. With his experience in software development and extensive knowledge of SaaS management, he writes mostly about emerging B2B technologies and their impact on the current business landscape. However, he also provides in-depth reviews on a wide range of software solutions to help businesses find suitable options for them.

Through his work, he aims to help companies develop a more tech-forward approach to their operations and overcome their SaaS-related challenges. FinancesOnline is available for free for all business professionals interested in an efficient way to find top-notch SaaS solutions. We are able to keep our service free of charge thanks to cooperation with some of the vendors, who are willing to pay us for traffic and sales opportunities provided by our website. The BI market continues to increase in revenue terms, up by 8.

But starting , the industry growth rate will start to decline possibly because of embedded BI being accounted to other software industries like ERP and CRM.

Enterprise BI will become a solid vertical as embedded BI is not robust enough to handle huge data volumes. We are seeing more defensive AI developments in the coming years, up to Defensive AI developments are focusing around data security and ethical AI. Hyper-automation, system engineering, big data analytics, and virtual assistants will be shaping the top BI systems. Casual BI users are demanding more interactive but easy-to-use BI mobile apps.

Developing a powerful mobile BI that can handle big data may prove difficult. BI and big data are converging with the former now able to process volumes of external and diverse datasets for predictive and prescriptive analytics.

Parsing big data is costly; thus, more companies are turning to Analytics-as-a-Service. Concise data visualizations to explore your data. Product Index. Identifying areas to increase profits and reduce losses has never been easier. Overview Benefits Part Numbers. Not applicable. Dealer Login To access additional technical materials, please log in.