A True Hybrid Cloud Platform

Where are we today?   Since the launch of Qlik Sense Cloud in 2014 we have seen rapid growth in our cloud community, which now includes over 100,000 users worldwide.  We continue to expand and improve our offerings and today we offer multiple

from Jive Syndication Feed https://community.qlik.com/blogs/qlikproductinnovation/2017/05/26/a-true-hybrid-cloud-platform

Horizontal Bar Chart Extension

Last year I blogged about our  Mobile Friendly Horizontal Bar Chart that we use in most of our mashups in the Qlik Demo Team.   Since then, many things have changed. For a start, if you have a mashup that uses many objects, you will see the

from Jive Syndication Feed https://community.qlik.com/blogs/qlikviewdesignblog/2017/05/26/horizontal-bar-chart-extension

Tech Tip Thursday: Dynamic Power BI reports using Parameters

Did you know that you can dynamically filter data in Power BI using parameters that are stored in an Excel workbook? In this video, Patrick from Guy in a Cube shows us how, using M Functions within Power Query and a gateway to enable data refresh. Check it out!

from Category Name https://powerbi.microsoft.com/en-us/blog/tech-tip-thursday-dynamic-power-bi-reports-using-parameters/

Marketing, Data and GDPR – What You Need to Know

In May 2018, the European Union will bring a new set of regulations into force on data privacy. The regulations have been discussed for years and will replace the current rules that are in the Data Protection Directive in the EU (the UK will need to adhere to this for any transfer of data from the EU).

GDPR - blogThese regulations will be supported by the Information Commissioner’s Office and will have a big impact on all companies that have customers in Europe. However, many marketers are either not aware of their new responsibilities, or they think compliance is solely an IT problem that won’t affect them.

What are these regulations and what do those in charge of customer data need to know?

The General Data Protection Regulation (GDPR for short) covers how personal data should handled. This includes how individuals should be informed on how their personal data will be used, how individuals provide consent for its use (“freely given, specific, informed and unambiguous” consent; so no more implied consent or opt-out), and that individuals should always have control over data about them. While much of this is not new as the EU Data Protection Directive covered this area, the GDPR adds more requirements, clarifies others and as a set of regulations provides a greater force of law.

The GDPR clarifies how to determine if information that you collect or process is personally identifiable. This provides organisations with greater clarity on what should be protected. It also clarifies that it’s not just about the information you hold, but the information that might be held downstream or in the public domain (i.e. can the combination of what you know and some other source be used to identify an individual).

There is also a category of ”sensitive personal data” that has additional requirements on the collection and processing of the data. This category requires “explicit” consent for its collection and use – a checkbox in the browser is not sufficient. As with the EU Data Protection Directive, this includes racial or ethnic origin, criminal record, membership in a trade union, political opinions, religious beliefs, and sexual preference, but in addition the GDPR adds genetic and biometric information.

Additional significant changes include the potential need for a Data Protection Officer with sufficient resources, executive access, and independence, and potentially large penalties (up to 4% of turnover or 20M Euros) for failure to comply with the GDPR.

All of these changes – and the increase in penalties – aims to minimize the use of personal information by businesses. Where this data is necessary, businesses should use techniques to minimise the risk of breach or misuse of the data. These include the use of encryption, anonymisation, and/or pseudonymisation.  Tokenisation is a form of pseudonymisation.  Anonymisation is best left to data scientists. All of these techniques are mentioned and encouraged in the GDPR.

Given how important data analytics is to marketers today, it’s critical to understand how GDPR will affect how you run analytics programmes over time.

For analytics, the availability of data is paramount. The more insight that you can get into customer behaviour, the more likely it is that you can get accurate forecasts and insights into other customers and prospects. Using this information can help with customer-experience services and recommendation services.

However, determining what is personally identifiable information and if the individuals have properly consented to it use can make this more difficult to run in practice. I always recommend that data collectors validate that they actually need to collect and process personal information, or pass it on to a third party for additional analytics. In the case of passing it on to a third party, any onward transfer requirements have to be validated to meet all necessary security and privacy requirements.

Running analytics programs

For marketers, getting initial consent on use of data is one hurdle. However, other issues such as the use of third-party data, and data deletion over time, also have to be considered. Putting the right processes in place for how you acquire and manage data should therefore be a priority.

To get this started, collaborate with your internal data privacy team. This will mean looking at your vendors to ensure that the appropriate legal language for data security and privacy is in place within your contracts. This is a requirement if you are transferring data to those vendors to process, even if they are not viewing it or sharing it.

Next, look at your approach to delivering analytics. Are you making use of marketing analytics services that take your customer data and provide results back to you? If so, you’ll have to check that they meet all these data protection requirements. Many suppliers are based outside of the EU, so be aware of the appropriate legal frameworks such as the EU-US Privacy Shield, EU model clauses, and binding corporate rules (BCR). These may change over time based upon legal decisions, such as the invalidation of the US-EU Safe Harbor framework by the European Court of Justice.

Awareness of where your data might be transferred should be a priority. It’s possible to run your own analytics services in-house, on a private cloud, or via public cloud services, so check how these options might fit with your own requirements on data privacy specifically related to requirements for onward data transfer.

Finally, be aware of how the right to remove consent for use (opt out) might affect your use of the data. Putting an appropriate plan in place, from the start, on how to remove customer records can help you in the longer term.

As more companies utilize data for helping make marketing decisions, the role of analytics will become more important. Making sure that your approach to analytics meets the necessary guidance on data security and privacy will therefore be essential.

This article was originally published in My Customer on April 25, 2017.

The post Marketing, Data and GDPR – What You Need to Know appeared first on Birst.

from Blog – Birst https://www.birst.com/blog/marketing-data-gdpr-need-know/

Tech Tip Thursday: Dynamic Power BI reports using Parameters

Did you know that you can dynamically filter data in Power BI using parameters that are stored in an Excel workbook? In this video, Patrick from Guy in a Cube shows us how, using M Functions within Power Query and a gateway to enable data refresh. Check it out!

from Microsoft Power BI Blog | Microsoft Power BI https://powerbi.microsoft.com/en-us/blog/tech-tip-thursday-dynamic-power-bi-reports-using-parameters/

Leave Data Where It Is

The Big Data ‘hype’ may have died down at this point but for many of our customers big data is still a really big deal.  Today, companies have a wide range of tools at their disposal for managing and processing big data but one aspect of working with big data remains a concern – that is how to make big data accessible, relevant, and interactive to every business user.  Most big data systems are great for processing big data in batch jobs or for supporting the quantitative elite but are just too slow to query in real time and work with interactively.  It is true that in some cases, this pain can be reduced but at great financial cost making it difficult to deliver the full potential of your big data investments across the entire business. 

Qlik On-Demand App Generation to the rescue!


Over the past few years, Qlik has worked closely with some of our largest customers to develop techniques that provide an interactive user experience from Big Data so that every user can benefit from these investments.  And, the best part, this technique works just as well on Qlik Sense as it does on QlikVIew.


As a simple example, imagine a telco company that has data from every touch point between every cell-phone and every cell-tower.  (That’s big data!)  A customer calls the telco call-center asking for help with a connectivity issue on their phone that they experienced last Tuesday.  The phone rep doesn’t really need ALL of the data in the big data store to do that analysis but they do need to be able to work interactively with the data that is relevant to the caller in real time so that they can help them.


On-Demand App Generation (ODAG) provides the ability for a user to first select a subset of data that they are interested in from a Big Data lake and then generates a detailed app with the relevant data for the user to explore interactively. 


In our example, the phone rep might select the caller’s phone number and all of the cell towers within a wide radius around the area where the caller was traveling last Tuesday.  Qlik On-Demand App Generation will then spawn a customized instance of the analysis app with just the data that is needed to help this customer.  Since the customized version of the analysis app is now in-memory, Qlik is able to deliver a tailor made highly interactive experience.  Why is this important?  Because this allows the phone-rep to work with that customer in real-time solving their problem and improving customer service. 


We will share more specifics about how to work with On Demand App Generation in both Qlik Sense and QlikView in the future. Stay Tuned!


Qlik On-Demand App Generation was actually introduced last June after working with a number of large customers to develop the technique.  Over the past year we have worked to provide more a more integrated solution which is what you will be seeing this June.

What’s Cooking @ Qlik

This information and Qlik‘s strategy and possible future developments are subject to change and may be changed by Qlik at any time for any reason without notice. This information is provided without a warranty of any kind.  The information contained here may not be copied, distributed, or otherwise shared with any third party.


ODAG is an incredible tool to have in your Big Data toolbox but there is still room for improvement.  In the future, our goal is to take this a step further delivering the best of both worlds – a direct connection back to a ‘live’ big data store and a highly interactive user experience that delivers the Associative Experience.


With On-Demand App Generation, we solve the performance concerns of working with Big Data but in order to request a different ‘slice’ of the data, users need to move back to the selection app and start over.  And, of course, working on the entire data lake is not possible using this model.


At Qonnections recently we were able to get a preview of just how this is expected to work in the future.


In addition to continuing to offer the On-Demand App Generation approach to Big Data, Qlik is working toward a solution currently referred to as Associative Big Data Indexing.  Imagine a future with the full associative experience on top of a big data lake without moving the data.  This model involves a parallel array of indexing engines optimized for Qlik style associative queries and speed. 

WARNING: The following picture does not exist today.  It is illustrative of an idea and a potential future state that should not be taken as a commitment by Qlik.  This information is provided without a warranty of any kind.


Data can remain located in the cloud, on premises, or even a combination.  And, the Associative Big Data Index can be reused across multiple apps so everyone across the organization can gain the benefits and insights in your big data investments.  We look forward to sharing more about On Demand App Generation and Associative Big Data Indexing in the future.

from Jive Syndication Feed https://community.qlik.com/blogs/qlikproductinnovation/2017/05/24/leave-data-where-it-is

Qonnections 2017 – It’s going to be a great year!

One week ago today we opened our biggest Qonnections conference yet with over 3,200 customers, partners, analysts, press and Qlik team members.  During the opening keynote, Rick Jackson, CMO, reinforced a theme that we at Qlik continue to believe is critical to the success of our customers in the changing BI landscape.

People + Data + Ideas = Possibilities


Lars Björk, CEO, shared what we have accomplished since Qonnections 2016 – a year of Qlik Sense® and Qlik® Analytics Platform (QAP) – including going from a public to private company, investing in our innovation, and continuing our commitment to changing the world. It’s this focus that has led to recognition by Fast Company as one of the most innovative companies for social good.  (This is a recognition that I am particularly proud of as an employee.)


Finally, Anthony Deighton, CTO, took the stage to share the new product roadmap and demonstrate some of what Qlik is working on over the coming year.  We not only got a preview of what is coming in June but also a sneak peak at what is coming beyond as well.  During this product presentation, Anthony focused on three key themes. 



What’s Cooking @ Qlik

This information and Qlik‘s strategy and possible future developments are subject to change and may be changed by Qlik at any time for any reason without notice. This information is provided without a warranty of any kind.  The information contained here may not be copied, distributed, or otherwise shared with any third party.

  • Leave Data Where It Is
    • Qlik has multiple strategies for dealing with Big Data today.  However, in many cases Big Data especially in the cloud needs a different strategy…one that doesn’t involve moving the data into Qlik’s in-memory engine.  WHAT IF SOMEDAY…. we could move the engine out to the edges?


  • A True Hybrid Cloud Platform
    • On-Premises OR Cloud is not the question….Companies rarely choose an all or nothing approach to cloud.  So, why should their BI vendor?  WHAT IF SOMEDAY you could seamlessly move between on-premises or cloud or both with your apps and/or your data?


  • From BI to AI
    • BI stands for Business Intelligence, but what does AI stand for?….If you answered “Artificial Intelligence”, you would have forgotten our vision – People + Data + Ideas = Possibilities.   WHAT IF instead, it meant “Augmented Intelligence”…. that is the ability to couple the intelligence of a cognitive rules engine with the experience, intuition, and know-how of your best and brightest.


I can’t be certain what next week or next year will hold, but I do know Qlik has people, data, ideas and a lot of possibility. I am already looking forward to next year’s Qonnections event!

from Jive Syndication Feed https://community.qlik.com/blogs/qlikproductinnovation/2017/05/23/qonnections-2017-its-going-to-be-a-great-year