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Embarking on a transformative journey into the cloud demands a partner who not only envisions a seamless passage, but prioritizes the safety and security of your digital landscape.
At Qlik, our commitment is grounded in the belief that your move into the cloud should not be just a technological leap, but a confident stride towards a secure and trusted digital future. As we continuously strengthen our platform with the latest data protection standards, our dedication towards Qlik Cloud is to provide more than convenience—it's about empowering your organization with the safest and most reliable cloud experience.
John Carroll, who leads the Qlik Engagement team at the Department of Employment and Workplace Relations of Australia shared with us his experience moving into Qlik Cloud:
“We use Qlik’s data analytics platform every day to influence government policy, inform operational decisions, and support program management. This new classification further propels our move to the cloud, allowing us to future-proof our operations.”
To learn more about how Qlik Cloud's IRAP assessment builds a foundation for AI, read the Press Release here. To learn more about the recent enhancements Qlik Cloud has achieved, read further:
New Assessments and Certifications:
IRAP Protected
ISO
While IRAP is an Australian focused security framework, ISO is a globally recognized standard. Many Qlik customers leverage ISO as their primary framework for evaluating security and compliance. Today Qlik is announcing that addition to our existing SOC 2 Type 2 + HITRUST accreditation, we recently achieved the ISO 27017 and 27018 Certifications for Cloud Security and Cloud Privacy, respectively.
Updated Certifications:
Summary:
In conclusion, at Qlik, our unwavering commitment to your cloud journey extends far beyond mere convenience. We are proud to offer not just a seamless transition, but a fortified path supported by the latest data protection standards. Your safety and security are at the forefront of our mission, and as Qlik Cloud continues to grow, we remain dedicated to evolving and expanding into new markets, extending our robust support to an ever-growing community of customers.
The Qlik Learning team have released a brand new qualification for you to demonstrate your Data Literacy skills. The new Data Literacy Qualification is a non-technical, product-agnostic exam, measuring an individual’s fundamental-level and applied understanding of skills and abilities to read, work with, analyze and communicate with data.
This exam is different to the pre-existing Data Literacy Certification. The Data Literacy Certification assesses mastery level competencies, it is more advanced and requires background and skills within data and analytics. The new Data Literacy Qualification does not require any background and can be taken by anyone. There are some suggested pre-requisites, but it is an exam that is much more accessible to those starting their journey in data and analytics.
The Data Literacy Qualification exam is a timed exam for which you have 1 hour to answer 30 multiple choice questions. If you would like more information on the exam topics covered and information on preparation resources, please go here.
To get started with the exam, visit the Qlik Learning Portal, then choose Assessments from the top navigation→ Qualifications → Data Literacy.
Once you have passed the exam you will receive a digital badge via Credly that you can share on you social channels to show off your skills! To access this exam, and an amazing range of both product-focused and product-agnostic learning resources, sign up to our Academic Program at qlik.com/academicprogram.
In my last post, I discussed the robust capabilities of Qlik Sense(QS) APIs to build out-of-the-box visual metaphors and ways to integrate them within Qlik’s ecosystem. A natural choice for developers while building QS extensions throughout the years has been the Extension API primarily using vanilla JavaScript, jQuery and AngularJS.
The Extension API consists of methods and properties used to create custom visualization extensions.
Enter… Qlik Sense’s Open Source Solution — Nebula.js!
Nebula.js is a collection of product and framework agnostic JavaScript libraries and APIs that helps developers integrate visualizations and mashups on top of the Qlik Associative Engine in QS Desktop, QS Enterprise on Windows, and SaaS editions of Qlik Sense. This tutorial specifically applies to the QS SaaS edition. Nebula.js offers developers an alternative to the 'Capability APIs' that have historically been used to create mashups. The tutorial will focus on developing a new visualization based on a user scenario using Nebula.js and the 3rd-party visualization library D3.js. Our target is to understand how we can leverage Nebula.js to build a QS extension object and bring in out-of-the-box visualization capabilities within the SaaS platform. This tutorial does not emphasize the D3.js programming part, but the motivation behind the visualization is discussed.
User scenario: An organization using Qlik Sense has a new requirement to develop a visual representation to understand high-dimensional mutlivariate dataset for their organization. Their dataset consists of numerical values, and they want to compare multiple features together to analyze the relationships between them. Based on these requirements, their Data Visualization Engineer presents to them the ‘Parallel Coordinate plot’.
Parallel coordinate plots (PCP) have proved to be efficient in effectively visualizing high-dimensional multivariate datasets. In a parallel coordinate, each feature is represented as vertical bars and the values are plotted as a series of lines connected across each axis. Their advantage is that the vertical bars(features) can have their own scale, as each feature works off a different unit of measurement. PCP provides insights into specific hidden patterns in data like similarities, clusters, etc., and allows for more straightforward comparative analysis.
Prerequisites:
Step1: Use nebula.js CLI to import the necessary packages. The command scaffolds a project into the /hello folder with the following structure:
Command:npx @nebula.js/cli create hello --picasso none
Step 2: Start the development server by running:
cd hello
npm run start
The command starts a local development server and opens up http://localhost:8080 in your browser. The benefit of having the dev server with Nebula.js is that it provides an interactive way to test and edit your extension without the need to iteratively deploy in QS every time a new change is made.
Step 3: Configure the data structure.
Visualizations in QS are based on a hypercube definition(qHyperCubeDef ). Therefore, any new visual object we want to bring into the QS ecosystem needs to have the data structure defined. With Nebula.js, we have the object-properties.js file that allows defining the structure of our object.
const properties = {
showTitles: true,
qHyperCubeDef: {
qInitialDataFetch: [{ qWidth: 30, qHeight: 200 }],
}
}
We also need to set a data target in the data.js file so we refer to the right hypercube definition(important to note in case you have multiple qHyperCubeDef objects).
export default {
targets: [
{
path:'/qHyperCubeDef',
}
],
};
Step 4: Developing the visualization extension using Nebula.js and D3.js.
QS Nebula.js specific code:
Now that we have everything ready, we start developing our extension with the custom visualization object using the index.js file from our project.
Note that Nebula.js and its primary package @nebula.js/stardust is built on the concept of custom hooks. This might sound familiar to people working with React.js. Hooks is a concept that emphasizes reusable, composable functions rather than classical object-oriented classes and inheritance. The primary hooks that we are dependent on for developing our extension object are described below:
The method that helps us in rendering our visualization object is the component()function. The component() function is executed every time something related to the object rendering changes, for example, theme, data model, data selections, component state, etc. This function can be compared to the paint() function in the Extension API.
To render our data, we first need to access the layout through the useLayout hook and then use it in combination with the useEffect hook. The hypercube’s qDataPages[0].qMatrix contains all the data(dimension and measures) used in the QS environment, and we will need to pass this data to our D3.js-based visualization.
component() {
const element = useElement();
const layout = useLayout();
useEffect(() => {
var qMatrix = layout.qHyperCube.qDataPages[0].qMatrix;
}
}
To see the data values and understand the structure of the qHyperCube, it is always a good idea to do a console.log(layout). A snippet shows values specific to our use case. Every time a new dimension or measure is added to our extension object, qDataPages[0].qMatrix is updated with those values.
The required dimension values for our chart are then extracted from the hypercube using the qText property from qDataPages[0].qMatrix like below.
var data = qMatrix.map(function (d) {
return {
PetalLength: d[0].qText,
PetalWidth: d[1].qText,
SepalLength: d[2].qText,
SepalWidth: d[3].qText,
Species: d[4].qText,
};
});
Our next step is to define the width and height of the visualization object, and capture its id. We will use this id to bind it to our element object from the useLayout hook as shown below:
var width = 1000;
var height = 400;
var id = "container_" + layout.qInfo.qId;
const elem_new = `<div id=${id}></div>`;
element.innerHTML = elem_new;
Finally, we make a call to the D3.js function from within the useEffect hook.
viz(data, width, height, id);
D3.js specific code:
The viz() function contains all of our D3.js code that allows us to draw a Parallel coordinate plot. First, we would need to append the SVG to the <div> that contains the id of our QS object, like below.
var svg = d3
.select("#" + id)
.append("svg")
.attr("width", width + margin.left + margin.right)
.attr("height", height + margin.top + margin.bottom)
.append("g")
.attr(
"transform",
"translate(" + margin.left + "," + margin.top + ")"
);
We then get all of the dimensions except Species to build our x and y axes.
var dimensions = Object.keys(data[0]).filter(function (d) {
return d != "Species";
});
var y = {};
for (var i in dimensions) {
var name_new = dimensions[i];
y[name_new] = d3.scaleLinear().domain([0, 8]).range([height, 0]);
}
var x = d3.scalePoint().range([0, width]).domain(dimensions);
To draw the lines for our Parallel coordinate plot, we will need to build the path function that would take a row from our qHyperCube and return the x and y coordinates of the line.
function path(d) {
return d3.line()(
dimensions.map(function (p) {
return [x(p), y[p](d[p])];
})
);
}
And finally, we bind everything with our SVG like below:
svg
.selectAll("myPath")
.data(data)
.enter()
.append("path")
.attr("class", function (d) {
return "line " + d.Species;
})
.attr("d", path)
.style("fill", "none")
.style("stroke", function (d) {
return color(d.Species);
})
.style("opacity", 0.5);
Step 5: Deploying the extension.
To build our project, we use the below command below to generates all QS readable files and puts them in a folder /hello-ext . This folder can then be compressed(.zip) and uploaded to the Extension section of SaaS console to be used within the QS environment.
npm run sense
If you are just getting started with Nebula.js, https://qlik.dev is a great place to review the basics and drill-down on related functions.
This project’s source code is made available at: https://github.com/dipankarqlik/Nebula
To help answer these questions, we are happy to share with you the capabilities of our Reload Analyzer for Qlik Sense SaaS!
The Reload Analyzer app provides insights on:
(Available sheets)
The Reload Analyzer uses Qlik’s RESTful APIs to fetch all the required data and stores the history in QVD files, allowing for efficient reloads and historical analysis.
A few things to note:
The app as well as the configuration guide are available via GitHub, linked below.
Any issues or enhancement requests should be opened on the Issues page within the app’s GitHub repository.
Be sure to subscribe to the Qlik Support Updates Blog by clicking the green Subscribe button to stay up-to-date with the latest Qlik Support announcements. Please give this post a like if you found it helpful!
Kind regards,
Qlik Digital Support Team
Additional Resources:
Our other monitoring apps for Qlik Cloud can be found below.
Edited 29th of January, 15:00 CET, added information on how to migrate to use a JSON key file, as well as updated the release date for on-premise from February to May 2024.
Edited 23rd of February, 15:10 CET, updated release date for Qlik Cloud release, which has been confirmed for the 6th of March 2024.
Hello everyone,
An upcoming update of the Qlik Sense Google BigQuery Connector will no longer support the use of a p12 file as the Key File. This is currently supported while Service Authentication is used as the OAuth mechanism. If you are using a p12 key file in the definition with this connection scenario, you will have to migrate to a JSON key file instead.
The latest version of OpenSSL, 3.0, has deprecated p12 as a legacy function. Therefore, while the new connector version will have a new driver supporting OpenSSL 3.0, it cannot support p12 key files anymore.
The easiest way to migrate is to create a new JSON key file in the Google Console. Then, the new key file can be used in the connection definition replacing a currently used p12 file. See Google Cloud documentation for more details on how to create and delete service account keys.
The updated Connector will be rolled out in Qlik Sense Cloud on the 6th of March, and in the May 2024 release of Qlik Sense Enterprise on Windows.
Thank you for choosing Qlik,
Qlik Support
Qlik Learning is excited to announce the release of our new Data Literacy Qualification Exam!
Data Literacy Qualification Exam is a non-technical, product-agnostic exam, measuring an individual’s fundamental-level and applied understanding of skills and abilities to read, work with, analyze and communicate with data. This is a timed, 1 hour, 30 question multiple-choice exam. See here to get more details on the exam topics and preparation resources.
To get started with the exam, visit the Qlik Learning Portal, then choose Assessments from the top navigation→ Qualifications → Data Literacy
Upon successfully passing the exam, you will earn a certificate of completion, a Credly digital badge for sharing on Social Sites and of course; bragging rights!
Questions? Feedback? Reach out to education@qlik.com
Happy Learning!

Marvel Heros

Amazing visuals using the new container

BI Developers

More a front end application

Testing Layout Container withot limits!

Design and creativity

Developers

Design and creativity

Abilities of the new layout container, Thinking outside of the box

Visuals make everything pop! Interaction is key

Bi Developers CEO CIO Marketing Business Users

This is more a visual presentation of the application
Alternate states in Qlik Sense allow users to make different selections on the same dimension throughout their app. This feature can be helpful when comparing data or displaying only the selected information needed.
Recently, while working on my college football app, I found a need for using alternative states. In one sheet of the app, two teams are being pitted against each other, showing information based around the team’s stats. With alternative states, I was able to assign each a state of ‘Team 1’ and ‘Team 2’ so that users could select which teams will be displayed and compared.
In this example, we have created a few KPI’s to display the various data points that were found relevant to a team’s success. In the image above, we have chosen alternative states for Team 1 and Team 2 for each of the filter panes on either side of the sheet. Likewise, we have assigned those states to the KPIs as well. This allows the user to choose a team from each filter pane and receive the data relevant to only those teams.
Additionally, these states can be used in conjunction with expressions to calculate needed information. For example, our chances of winning are calculated by dividing Team1’s Overall Points by the sum of both teams. The Overall Team Points are automatically factored into the expression when selected in the filter panes.
In a different use case, we could take on the mindset of a high-level manager of a sales team. In this instance we have two salespersons being compared in various metrics. This could be used to see who is deficient in some areas, and who is leading in others. Maybe these two salespeople could help each other, assisting where one is thriving, where the other may need some help.
With a change in the filter pane field, we can do the same for a city, comparing two cities’ metrics against one another. In the mind of our sales team manager, the ability to compare cities could show how different geological factors affect sales trends. Maybe more camping equipment is sold in one area than another, so those products could be allocated there instead to further sales.
There are only a few use cases for alternative states, and there are many more that you can use within your own apps. How do you plan to use alternative states?
Qlik Sense Map charts are used to geographically display data related to countries, cities, states, regions, or particular geolocations (etc…). Maps offer different ways to present your data by first setting a base layer, then adding multiple layers to the map which are specific locations highlighted in multiple ways including Area, Points, Lines, Density, boundaries etc..
You can add as many layers as you want. These layers are comprised of dimensions and measures that allow to efficiently present geographical distribution of values related to locations in order to display a data story.
Using different base maps can enhance the way data is displayed and aid in analysis. You can choose from:
When including multiple layers in map chart, it might become hard to interpret data. In that case, you can address this by controlling at what zoom levels different layers appear or have layers that appear only if other values in a drill-down dimensions are selected. This allows to create multiple levels of detail as you make selections and zoom in and out or locations of interest on the map.
Let’s create a map that relies on Zoom to reveal different layers.
The result:
Let’s create a map that uses a drill-down dimension to display layers based on selection. Keep in mind that Drill-down dimensions should have the fields in order of highest geographical are to smallest geographical area.
The result:
Tip:
If you load data and it appears incorrect like below:
Head to Location, switch off Scope for location from Auto to Custom.
Change Location Type to “Administrative Area (Level 1)” in our case. Then, change Country to your location, in our example it’s ‘US’
Let’s create a map with multiple background layers using a TMS and two WMS.
Important:
Keep in mind that when using URLs for TMS and WMS formats for background layers, these URLs that contain resource requests to external resources must have its origins allowlisted in the Content Security Policy, else the resource will not be loaded. WMS resources must have both image-src and connect-src directives allowlisted. More Info here.
The Result:
The QVFs for all three advanced examples can be found below. You can load them to your Qlik Cloud tenant, investigate the chart settings, and tweak the configurations to practice these concepts.

Enabling users to slice & dice metrics as they please, this game-changing visualization unlocks root cause analysis & ad-hoc exploration of complex datasets on the spot.

Become a master at crafting smaller, yet more impactful dashboards that even non-techies can navigate intuitively. And while they explore & make decisions, just kick back, take a sip, and enjoy life.

BI Developers & Analysts; Managers & Heads of Visual Analytics & BI Solutions; Qlik Developers & Data Engineers; CIOs & IT Directors.

Elevate your data mastery & earn your business users' love for revolutionizing their data analysis journey!
🔗 > DOWNLOAD DEMO APP (.QVF) <
These individuals are some of our most active participants of the Qlik Academic Program who fully utilise the free software, training resources and qualifications that we provide to university students and educators. The members of our 2024 class are:
Dr Nassir Ibrahim
Marcin Stawarz
Blerim Emruli
Javier Leon, Adjunct Professor
Sumitra Purushottam Pundlik
Priscila de Jesus Papazissis Paolinelli
Jacek Harazin
Angelika Klidas
Dr K Kalaiselvi
Angel R Monjarás
Daniel E. O'Leary
Meet the Qlik Academic Program Professor Ambassadors for 2024
We are thrilled to be recognizing the efforts of these individuals to help the Qlik Academic Program to achieve its mission - to create a data literate world, one student at a time. Each ambassador has been selected through a self-nominated application process, where they were required to answer various questions covering their motivations for becoming an ambassador, and to evidence their passion for upskilling their students in analytics over the past 12 months. This year, we are excited to select another 11 ambassadors, 5 new ones and 6 returning ambassadors whose efforts continued to impress us. By way of thanks for their efforts our ambassadors will receive exclusive benefits such as webinars and discussion groups with Qlik leaders, opportunities to showcase their experience with the Qlik Academic Program and the chance to grow their network with other educators across various fields and geographies.
Throughout 2024 our ambassadors will continue their advocacy for the Qlik Academic Program and help us to reach even more students and educators with our free resources. Stay tuned over the coming months for more in-depth profiles on each of our ambassadors, and get to know who they are, what they teach and why they are so passionate about bridging the data literacy skills gap! Learn more about the program and how to apply for future classes.
企業のビジネス活動において、データはこれまで以上に必要不可欠な資産となっています。増え続けるデータを管理・統合・分析し、データでアクションを起こす必要性が増している現在、成功している企業はどのようなデータ戦略を実行しているのか?
本 Web セミナーシリーズでは、Qlik でデータからアクションを起こすデータ主導のビジネスで成功しているお客様より、課題から導入の経緯、デモンストレーション、活用例などをご紹介します。
株式会社 QTnet では、Excel や Access で利用してきたデータ活用を 2010年から本格的に BI ツールである Qlik によるデータ活用へ移行しました。しかし、データ抽出が大半でデータの可視化や分析、活用は一向に進まない状況でした。2019年、Qlik Sense の導入を契機にシステム部門でデータ整備からアプリまで一貫した提案型の開発に挑戦しました。ところが、穏やかな船出とはいかず、業務部門との信頼関係を築くことからスタートしました。
今回は、ユーザと共に作り上げてきたアプリについて、その成果(自動化や可視化を達成)に関する具体例について、デモを交えて紹介します。
Increased flexibility when accessing SaaS applications and file storage services
Qlik has expanded the governance capabilities of Qlik Cloud Analytics by significantly increasing the number of connectors that can support user-defined credentials. Instead of a generic company ID, user-defined credentials help ensure that data access will be governed based on what has already been defined in the source system for each user.
Previously, Qlik Cloud Analytics only provided this option to some enterprise applications, such as Salesforce, and ODBC-based connectors (ex. Oracle). Now customers can define, on a connector-by-connector basis, whether user-specific credentials will be required to access many of their SaaS applications and file storage services.
User-defined credentials will work with all the relevant authentication options that are available in each connector (ex. OAuth, Access Key, Key File, etc.). And these personal credentials can be saved and used across multiple connection definitions for the same source.
This new capability has been added to the following connectors:
SaaS applications
SaaS file storage services (including related metadata)
Effective October 2, 2023, all feature requests will be submitted via the Qlik Community. Requests are entered as an “Idea” and are evaluated by Product Managers. Product Managers will communicate with you via the idea throughout the lifecycle. With this change, feature requests are no longer required to be submitted via the Talend Support Portal.
What you will need to do:
If you have any questions about this new process, please comment below or email QlikCommunityAdmins@qlik.com.
They say that January is a time for new beginnings, and we took that seriously this year! We have some exciting news and updates this month, including…
Qlik Introduces a Bold New Look!
January 16th, 2024 marked a pivotal moment for Qlik as we launched our new brand and website to the world. This transformation reflects our story of growth, innovation, and change. But more importantly, it is an evolution of how you can experience Qlik: our shared values, our vision, and our expanded product portfolio to deliver real business value for you. It is also our commitment to you – to be the catalyst that empowers you to leverage data for substantial business outcomes.
Read our announcement blog to learn more about Qlik’s brand transformation.
Bridging the Trust Gap in Generative AI: The Big to Better Data Imperative
It’s finally here! On January 17th, Qlik released the top 10 trends in BI, Data, and AI for 2024. You can watch the full webinar here, or for a more personalized approach, explore each trend on its own through our Trends 2024 digital experience.
The Official AI Reference Guide
Getting caught in the hype around the potential of AI is understandable, but like many technologies, learning to walk before you can run is essential. To help, Qlik put together a conversation AI glossary…
Click here to explore nearly 50 key AI terms you need to know when working with data and analytics.
Join Us For Qlik Connect!
Now through February 15th, save $300 on your Qlik Connect registration. This is a valuable opportunity to enjoy a discount and be part of an event that will play a role in shaping the future of data.
Tips & Tricks of the Month: New Year, New Badge as Analytics Expert!
Join our upcoming spring cohort; a collaborative learning environment led by our expert instructors including shared experiences with other Qlik customers and get your digital badge in 15 weeks. Learn More & Register.
The report forecasts that between now and 2027, businesses predict that 44% of workers’ core skills will be disrupted, because technology is moving faster than companies can design and scale up their training programs. Our Academic Program gives the students of today a chance to get to grips with our industry leading took Qlik Sense, so that they arrive in the workplace a step ahead of the rest and ready to thrive. By using the program to supplement their university courses, they can arrive with the skills needed in the modern-day workplace and save the time and cost of upskilling later. Students can train on the learning resources built by us and used by customers and partners to get themselves workplace ready.
When the World Economic Forum ran this survey in 2023, they created a list of the top 10 skills deemed to be the most important at the time of survey. These are a mix of cognitive skills, self-efficacy, management skills, technology skills and working with others. Number six on the list was technological literacy, however when they looked at skills on the rise in the next five years, technological literacy moved up to number three. This skill is the third fastest growing core skill, and it refers to the knowledge and ability required to effectively and responsibly use technology tools and resources. Many individuals at university are already learning to acquire and communicate information in a fully digital environment. But they will need to transfer these skills to a professional workplace and be expected to interpret this information into insights to inform business decisions. Most business are now using data solutions in order to support this process; students will need to go into the workplace with an understanding of how this technology works.
In addition to the need for candidates with technological literacy, the future workplace needs workers who are also skilled in AI and big data. Ranked number seventh for fastest growing skill, AI and big data will see a 60% growth in demand by 2027. As part of the Qlik academic program, members can start to train on Qlik Sense, our market leading tool for data analytics. By following some of the short training videos and learning about basic functionality, students can go into the workplace with an understanding of the benefits of data solutions and show their employers they have taken the initiative to upskill themselves in big data.
The Qlik academic program offers a fantastic opportunity for students to start their professional learning journey in data and technology and leave university in the next few years with the skills needed in the workplace. Our courses on data literacy support the hard and soft skills needed in the future workplace. Even if you are student pursuing a course outside of IT, taking a couple of free courses in data visualizations and data literacy could help you become more employable after university. If you’re unsure of where to start with your 2024 learning journey, then the best thing to do is to take our data literacy persona assessment, and then explore some of the courses that interest you. To start accessing these courses go to, qlik.com/academicprogram and apply to our free program.
多くの日本企業ではビジネス基盤として SAP ERP を導入しています。「AI活用」「データドリブン」などのビジネス環境の大きな変化に伴い、データ基盤のモダナイズが喫緊の課題となっています。こうした中で柔軟な運用とコストメリットを求めてシステム基盤をオンプレミスからクラウドへ移行する企業が増えています。特に SAP ユーザーは RISE with SAP により、クラウド化・モダナイズを進めています。これは、より効率的なシステム環境の構築によりコストと時間を節約する機会にもなります。
典型的な SAP 環境を見てみましょう。一般的に、ある Production 環境をリリースする際には、品質管理やトレーニングのために、そのサブセットとなるシステムを構築します。また同じデータセットは開発環境にも必要です。このように同じような環境を複数構築するにはコストと時間がかかります。
Qlik が提供する Gold Client はこのプロセスを効率化します。
Qlik Gold Client を使えば、基盤とデータのメンテナンスコストを削減し、開発、テスト、トレーニング環境を効果的、かつセキュアに構築できます。ビジネス継続性を損なうこともありません。
事例を一つご紹介します。顧客がデジタルトランスフォーメーションとエネルギー転換の課題に対応できるよう支援している Vinci Energies 社は Qlik Gold Client により SAP S/4HANA へのマイグレーションを非常に効率よく実現しました。戦略的なグローバルデジタルトランスフォーメーションを支援するために SAP S/4HANA への移行を希望していた同社は、本格的な移行を行う前に軽量なアーキテクチャでテストできるデータの小さなサブセットを作成するために Qlik Gold Client を使用しました。
同社は、DVP S/4 HANA のデータセット環境をゼロから作成し、3ヶ月分のデータと 20 の企業コードのデータ転送をわずか 8時間で行いました。Qlik Gold Client により、ゼロから手作業で行うことなく、変換済みの DVP システムを非常に迅速に作成することができたのです。SAP 環境間のデータ転送を検証したところ、すべてのオブジェクトと関連データが正しく転送されており、Qlik Gold Client は使い方が簡単で、高速かつ信頼性の高いツールであることが証明されました。
本事例はオンプレミスの事例ですが、もちろんクラウド移行の際にもご利用いただけます。ご興味をお持ちの方はぜひ Qlik へお問い合わせください。
Hey guys, I wanted to mix it up a bit and instead of focusing on direct features, functions and capabilities – I wanted to provide a demonstration that focuses on outcomes. In other words, a solution to a particular business problem and how I could achieve it using Qlik.
Introduction
You will see how I use AI and conversational analytics to collaborate in real-time with my colleagues to get context to help me explore my business problem further and how I can take action on my findings immediately by notifying and integrating with my valued partners, all from one platform. I even use a little generative AI with Amazon Bedrock as a fun example to show you the art of the possible.
Summary
To recap we started by using Microsoft Teams integrated Qlik’s AI based conversational analytics to inquire about open orders that our reps are working on. While speaking with the rep, we discovered that we had 1 order with an excessive lead time because of a part shortage and could not complete the product. Another inquiry showed that other reps and orders are also effected by this part shortage. We dove deeper into the analytics application where we integrated the ability to place an order directly from the app to communicate with our parts vendor using Slack and Generative AI to generate the order notification. Obviously this is a simple and fun scenario but you can see how powerful the Qlik platform is and how it can integrate with other systems to produce results and take action where and how you work. I’d love to hear your stories.
Have you integrated multiple components of Qlik together to produce meaningful outcomes? Let me know in the comments.
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