Data Stream Analysis (DSA): How to have and keep insights in your Data

Imagine 2030 where Data is created 24/7, day & night, on the workfloor, on the road or even maybe at home. Every machine, building, device, person is packed with a multitude of sensors. Digital Twins of all assets exist and are used for Virtual Rreality Trainings, remote operation,… Augmented AR is passing live feeds over the infrastructure to assist the worker in his daily tasks wherever he is.

We are now at the beginning of this age where Data is turned into value and building a more sustainable world where we live in.

To be able to deliver this we need to have insights in the Streams of Data flowing over the increasingly complex environments and technologies. Future landscapes will have Data stored in hybrid environments, Edge and multiple cloud environments. These landscapes will grow not only in Data volume being structured or unstructured but also in Realtime use of Live Data with an increasing flood of Data with an anticipated growth of 530% to 175 zettabytes in 2025.

This increasing complexity makes it difficult having a single pane of glass of these Data Streams making it harder to make profound decisions based on insights and advanced analytics.

Managing these Data Streams effectively becomes more challenging, thus elevating investments and operational costs. At the same time the risks involved are increasing in terms of data loss, data breaches, compliancy,….. Customers & Partners have more and more questions:

  • How can I have a single pane of glass of my Data on my Cloud Environments, Storage Environments or Backup Environments?
  • When will we run out of storage on these environments?
  • Do we have the necessary performance to handle these Data Volumes?
  • Can we optimise and have orphaned capacity that can be reclaimed or repurposed?
  • Are my cloud assets protected?
  • Is all of my essential Data from all my environments replicated on my backup?
  • Who or what is consuming my storage?
  • Can we optimise and have cloud workloads that can be decommissioned  to reduce costs?

With the DATA STREAM ANALYSIS Service from Fujitsu we can support our partners, their customers and our customers in their current and future environment with advanced analytics, one dashboard bringing all information together to make the right decisions at the right time:

  • Infrastructure Optimization
Monitor you Data Streams performance across your hybrid environment. Optimize storage usage, when will we run out of storage, what is causing delays,…
  • Unified visibility
Show IT relationships in one Single pane of glass. Who or what is consuming storage? Consolidated view of the IT infrastructure? Which Application by business unit are consuming IT resources the fastest?
  • Comprehensive chargeback
Chargeback your internal usage to the different departments or to customers
  • Cloud cost optimization
Which application workloads are good candidates for cloud migration? Which cloud workloads can be decommissioned to reduce costs?
  • Data Protection
Compliance and risk mitigation:  Are my cloud assests protected? Which clients does my backup software not know about? Which test/dev systems am I overprotecting?
  • Service Level Agreements
Are the different SLA’s met? Are we risking penalty’s?

Keep your costs in hand

First you need to make your storage costs as a whole cost efficient. In other words, you need to manage available capacities. This can be either on-prem or in the cloud. This makes it possible to see if there is a lot of empty space on the systems in your infrastructure. Instead of purchasing new storage, you can still use this unused capacity. For example if all-flash arrays are used as backup media, you can quickly rectify this by gathering the right insights.

DATA STREAM ANALYSIS is also vendor-agnostic. No matter what hardware is included in your infrastructure, the relevant insights can be extracted. You do not need a separate analytics application from every hardware vendor. This of course results in cost savings.

Finally,a tool such as DATA STREAM ANALYSIS gives you clear insight into who consumes what within the organization and therefore also into the costs that this entails. This in turn can be converted into clear reports for management, to see where resources are being used effectively and efficiently.

In addition, it can also be used for an organization-wide adoption of IT-as-a-Service. If you can see which parts of your organization are paying too much for what they purchase, then you can settle this with them. This chargeback works for on-prem or in the cloud.

Minimise risks

Secondly, you can limit risks by having insight into all your systems. Think of using predictive analytics to predict system failure. To do this, you obviously first need the data/logs of the systems, otherwise you have no idea what is going on. If you do this properly, you can replace components before their failure causes a problem. Especially if you work with SLA’s, you obviously want to minimize downtime and preferably eliminate it.

When using the “break-fix method” you are simply too late. Nowadays we need prediction. Automation and predictive analytics are crucial for reducing RTO and RPO or Disaster Recovery. With predictive analytics, you can make a disaster a lot less serious or perhaps even avert it. With automation, you get back on the air much faster, especially if you know where the problem lies thanks to the right analytics and insights.


The DATA STREAM ANALYSIS service is developed in such a way that it integrates with your existing tooling. This way you can link it to a CMDB, but also to an ITSM solution such as ServiceNow. It is important to keep in mind that DATA STREAM ANALYSIS does not actually look into the log files it collects, but only at the outside. That makes it an essentially different tool than, for example, Splunk. The idea is that DATA STREAM ANALYSIS’s data ends up in the datalakes of the organizations that use it, after which other tools can also use the data.



In order to get a complete picture, you need to be able to connect to all the other tools you may encounter in the infrastructure. Otherwise the analytics and therefore the insights of DATA STREAM ANALYSIS will not be of much use to you. That is also why the SDK is live, which makes it relatively easy for organizations to on-board their own environments.

As a result, you receive an analytics platform where every organization with questions around issues such as cost management, risk management and compliance has something to gain. Whether it’s Tier 1 or Tier 2 data and whether it’s on-premises, in the cloud, or in hybrid environments, it can all be made transparent. As an organization, you maximize the value of your investments and you know for sure that everything is in place. This will become even more important in the increasingly complex infrastructure that more and more companies are encountering.

Be ready now for your future Data Streams where the value of Data will only increase!



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