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Business Intelligence: The 10 Major Trends that are Shaping 2017

In 2016, the phenomenon of self-service data analysis invaded the corporate world. The IT department has begun to leverage different technologies for growth and scalability. Business users, on the other hand, have taken a collaborative approach by sharing their data more and more. In 2017, this self-service analytical culture continues to grow and become the standard in business, and the technological tools supporting this evolution are becoming commonplace.

1. New generation BI will emerge as the new standard

By democratizing data analysis, companies have already begun to make the transition to new decision-making tools. As Gartner explains, they have taken a decisive step by freeing themselves from the IT-centric platforms. With reliable and scalable platforms, even novice users can explore controlled data and improve collaboration by sharing their discoveries. In 2017, the new approach to decision support will become a priority for all companies, from large multinationals to smaller start-ups.

2. Collaborative analyzes will take center stage

2017 will mark the end of the era of one-way flows of information and sharing data as static PDF or PowerPoint files. Users will be able to share their data live and interactively and rely on it to guide their decisions. They will take advantage of the Cloud and other sharing features, such as email alerts and subscriptions, to stay informed. Finally, they can integrate their dashboards with other applications used in the company to better reach the intended audience. Users will therefore have to perform various functions, from using data in their dashboards, to carrying out their own ad hoc analyzes or to sharing their discoveries.

3. All data will be good to take

By 2017, the value of the data will no longer be dependent on its volume or priority. Whether Big Data or a simple Excel spreadsheet, the important thing is to allow users to quickly and easily access the many types of data to explore, find answers to their questions and improve their results. Business users will no longer have to wonder if their data is stored in Hadoop, Redshift or an Excel file. They will benefit from a complete overview of their analysis, regardless of the number of data sources used.

4. Self-service in the preparation of data

While self-service discovery has emerged as a new standard, data preparation has traditionally remained the prerogative of IT and data experts. But this will no longer be the case in the coming months. Usual preparation operations, such as hashing data, importing JSON and HTML files or cross-checking databases, will no longer be reserved for specialists. This change will raise new governance issues but many IT groups have already seized this opportunity. IT can thus ensure that the entire enterprise has access to the data and that users are working in a secure data environment.

5. Analytics will gain ground with built-in BI functionality

In 2017, analytics will become more general and will enrich the business processes. They will often be made available to people who have never used data, such as in-store sellers, call center employees or truck drivers. Integration of decision support features will expand the scope of the analytics to the extent that users will no longer be aware of their presence, which is quite similar to using predictive analytics to recommend videos on Netflix or tracks on Pandora.

6. IT will become the company’s hero

In 2017, the IT department will become an essential and decisive link for the future of the company. Indeed, for a long time, IT was caught up in the preparation of reports to meet the demands of the different operational units. Today, IT has the opportunity to break his chains and take on the role of facilitator, taking control of the transition to a self-service and scalable analytical environment. According to Gartner, in high performing companies, analysts are partners in whom other services have confidence. IT provides the flexibility and agility the company needs to innovate, while ensuring the right balance with governance and data security.

7. Use of data will become more natural

In 2017, communication with data will become more natural, partly due to improvements in areas such as natural language processing and automatic text generation. Natural language interfaces will complement the range of decision support tools and make data, graphics and dashboards more accessible by enabling users to interact with data through natural language and text. Gartner believes that this is the next step in the transition from standard reporting to narrative reporting.

8. Transition to the Cloud will accelerate

As companies move their data into the Cloud, they also realize that they have to do the same with their analytics. Data warehouses in the Cloud, such as Amazon Redshift, will continue to be privileged for data hosting and Cloud scans will become commonplace. Many companies will continue to deploy a hybrid architecture that combines cloud and on-premise solutions, but Cloud analytics will gradually emerge as a faster, more scalable solution.

9. Advanced analyzes will become more and more accessible

Business users have acquired a know-how in the field of data and advanced analyzes have become more accessible. These two phenomena will combine and the advanced analyzes will no longer be reserved for data specialists. Business users are already benefiting from powerful analytics such as k-means, clusters and forecasts, and will continue to develop their analytical skills.

10. Knowledge of data will become a core competence

In 2016, LinkedIn identified decision support as one of the skills most sought after by employers. In 2017, data analysis will become an essential skill for professionals from all sectors, as well as the use of Microsoft Word, Excel or PowerPoint. To respond to this need, analytical reasoning and data will emerge in school and university curricula and the use of decision-making platforms will spread to the world of work to facilitate decision-making at all levels .

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