1.Collaboration mining appearance
Due to the global epidemic of the new colon virus infection, collaboration and BI have become inseparable.With the transition to work from home, it has become indispensable for many companies to quickly incorporate BI into workstreams and productive apps such as Teams, Slack, and Zoom.In addition, the novice of physical spaces has increased the opportunity to collaborate with external stakeholders.According to a PWC survey, almost four out of five highest executives are convinced that remotely collaboration will continue after the global epidemic of the new colon virus infection.
However, there are other important challenges besides collaborating with insights and collaborating at the end of a series of tasks.You need to start collaborating early until you get an exploration and discussion after generating derivative data and reach an insight that can take action immediately.There is nothing to prevent data from sloring as a collaboration.As the collaboration expands throughout the analysis work, it will be able to look at the mechanism, improving collaboration methods related to data, networks, and processes.In other words, as you have learned data and process extraction, you will see the appearance of "collaboration mining".This allows you to track your decisions and get important auditivity, and to enhance your trust with multiple stakeholders.
2.The end and development of the dashboard
Recently, I often hear about the end of the dashboard.Anyone can display KPI and visualize data.
However, there is a major difference between a mere KPI monitoring and a detailed investigation analysis using an interactive and excellent expansion analytics application.It is more important to clarify the discovery that indicates the direction.
So how is the dashboard evolving?One is that the KPI has shifted from the delay index to the preceding indicators, and analyzing the main promotion factors is being analyzed.Advanced situation recognition is possible, and it is very coordinated.Creating an advanced alert that immediately grasps the change in data makes it possible to recognize the situation.Then, AI determines where the data is associated with the situation and where to pay attention.
In terms of collaboration, the dashboard has evolved into an analysis hub that converts the distributed data from Insight, making it a space where machines, processes, and collaboration intelligence can coexist.As a result, the creator of the information and the user can be integrated and cooperated with external stakeholders as needed.
3.Providing a BI that can explain the data system (Data Linage)
For many years, the analyzer has had a hard time explaining the indicators and the data behind KPI calculation.And this problem continues to worsen because the data has been fragmented not only in the company but also outside the company.
I don't think it will actually occur and will not happen in the future, but imagine that all data is collected in one place as an experiment in thinking.Still, you can't get one truth.This is because the data changes at the speed of nanoseconds, and new changes to be explained are constantly taking place.
At present, further distributed data architectures have appeared, and it is important to enhance data management such as data systems, impact analysis, and control, and to enhance data observation.In a world where multiple truths are related to each other, the lineage is extremely important in order to provide data from multiple perspectives to provide reliability and explanatory ability.
It is also useful for associating analysis with each other with multiple data sources and large platforms.If you can visualize where the data comes from or at what stage of the life cycle, you will be confident and trusted and act based on the insights derived from the data.You will be able to do it.
4.Costs that are highlighted by acquiring speedy insights
As the cloud -day toweahous house and data lake have been renewed, and spreading widely, the opportunity to perform queries directly in a huge amount of data has increased.A powerful tool for finding data has appeared.
However, using this method can increase the cost of cloud computing.In addition, performance also occurs.Rather than using only live query, you need data management and analysis approach according to frequency and delay requirements.If you look at the typical query "heat map", most of the questions are related to search, so you can run in memory without updating in real time.
On the other hand, more complex queries may need computing at the data source level.In terms of data integration, it is necessary to be able to select whether to update / combine data continuously, even if the computing cost is high, or to display the cost that reduces the cost.
From an analysis point of view, you should be able to choose whether to use a live query even if the computing cost is high or to search for in memory that can be high -speed and low cost.If you are aiming for a true data -led type, you need to consider how to make an appropriate query in an appropriate place, as both the speed of the insight and the cost per insight will increase.
Five.The appearance of distributed cloud
For the time being, the status of the data is thought to be in a confused and hybrid state.According to 451 Research, most companies are looking for IT assets that are not only comprehensive solutions for IT needs, but also for various task load costs, performance, and control requirements.(reference)
There is a reason for a special work load.The process may be faster on the edge side.Compliance is essential.Security is more important than ever.China's new data privacy method will be one of the most strict laws in the world.In Europe, a huge GAIA-X project has developed a foundation for integrated open-dating torpa filas for the purpose of connecting integrated infrastructure and distributed infrastructure to the same type of easy-to-use system.Distributed and hybrid clouds continue to have the following needs.
1) Hardware can be installed locally 2) Solving the disagreement in the cloud chain in the unified management and user interface 3) multiple cloud hypers when performed in the correct way.You can expand the scaler to reduce the dependence on the business
Distributed cloud infrastructure enhances the ability to safely and reliably perform both access and sharing data that are related to each other.
Gain knowledge and ability to respond to rapid changes
If the market is dominated by a small number of powerful value chains, you will not be able to fight alone.Build a partnership to build a value chain, which combines new architecture approaches, interoperability, and open platforms using APIs, bringing out unprecedented opportunities.The generated data and insights become a common currency, which can be flexible to the success of the company and partner.To take this approach, you need clear rules, common purposes, long -term perspectives, and change of mindset.Now is the time to fuse strongly.
Hiroshi Imai
Clicktech Japan Country Manager
Born in 1970.He joined Japan IBM in 1992 and was active as an American football player until 1999 with sales.After working at SAP Japan and Microsoft Japan, he became the General Manager of EMC Japan Data Protection Solutions Division since 2014.Incumbent since October 2019."Passion", "Play to Win", and "One Team" are the inscriptions on the right.
