Visual analytics with Qlik Sense® Cloud make it easy to uncover valuable business insights. Learn the basics and get the answers you need, right now.
With Qlik Sense® Cloud, there are no downloads, no hassles, and no catches – just reliable insights for your business. And it’s ready right now, at a price you can afford. In this SlideShare, we break down the basics of Qlik Sense Cloud, including its unique associative model, the ease of collaboration, and compelling, interactive visualizations that help you tell persuasive stories. Find out how to get the answers your business needs, right now.
Slides: Success Stories for Data-to-CloudDATAVERSITY
Companies are finding accessing data from a variety of sources can be labor-intensive and costly. Oftentimes these companies are looking to cloud solutions, but are then finding the traditional architecture brittle when trying to move data to the cloud, which can drain organizations of time and resources.
Join this webinar to hear several company success stories, the data-to-cloud issues they were encountering, and the steps these companies took to bring their cloud architecture to a successful, real-time analytic solution unlocking massive amounts of fresh enterprise-wide on a continuous basis.
In addition, you will learn how to:
• Modernize the ETL process to one that’s fast, flexible, and scalable
• Supply users with up-to-date, accurate, trusted data
• Increase your time to value with data in the cloud
• Best practices on how to minimize resource overhead
Join CCG for our Data Governance (DG) Workshop where CCG will introduce their Data Governance methodology and framework that enables organizations to assess DG faster, deriving actionable insights that can be quickly implemented with minimal disruption. CCG will also discuss how Microsoft Azure Solutions can be leveraged to build a strong foundation for governed data insights.
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
Modernizing to a Cloud Data ArchitectureDatabricks
Organizations with on-premises Hadoop infrastructure are bogged down by system complexity, unscalable infrastructure, and the increasing burden on DevOps to manage legacy architectures. Costs and resource utilization continue to go up while innovation has flatlined. In this session, you will learn why, now more than ever, enterprises are looking for cloud alternatives to Hadoop and are migrating off of the architecture in large numbers. You will also learn how elastic compute models’ benefits help one customer scale their analytics and AI workloads and best practices from their experience on a successful migration of their data and workloads to the cloud.
Data-Ed Slides: Best Practices in Data Stewardship (Technical)DATAVERSITY
In order to find value in your organization's data assets, heroic data stewards are tasked with saving the day- every single day! These heroes adhere to a data governance framework and work to ensure that data is: captured right the first time, validated through automated means, and integrated into business processes. Whether its data profiling or in depth root cause analysis, data stewards can be counted on to ensure the organization's mission critical data is reliable. In this webinar we will approach this framework, and punctuate important facets of a data steward’s role.
Learning Objectives:
- Understand the business need for a data governance framework
- Learn why embedded data quality principles are an important part of system/process design
- Identify opportunities to help drive your organization to a data driven culture
Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Slides: Success Stories for Data-to-CloudDATAVERSITY
Companies are finding accessing data from a variety of sources can be labor-intensive and costly. Oftentimes these companies are looking to cloud solutions, but are then finding the traditional architecture brittle when trying to move data to the cloud, which can drain organizations of time and resources.
Join this webinar to hear several company success stories, the data-to-cloud issues they were encountering, and the steps these companies took to bring their cloud architecture to a successful, real-time analytic solution unlocking massive amounts of fresh enterprise-wide on a continuous basis.
In addition, you will learn how to:
• Modernize the ETL process to one that’s fast, flexible, and scalable
• Supply users with up-to-date, accurate, trusted data
• Increase your time to value with data in the cloud
• Best practices on how to minimize resource overhead
Join CCG for our Data Governance (DG) Workshop where CCG will introduce their Data Governance methodology and framework that enables organizations to assess DG faster, deriving actionable insights that can be quickly implemented with minimal disruption. CCG will also discuss how Microsoft Azure Solutions can be leveraged to build a strong foundation for governed data insights.
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
Modernizing to a Cloud Data ArchitectureDatabricks
Organizations with on-premises Hadoop infrastructure are bogged down by system complexity, unscalable infrastructure, and the increasing burden on DevOps to manage legacy architectures. Costs and resource utilization continue to go up while innovation has flatlined. In this session, you will learn why, now more than ever, enterprises are looking for cloud alternatives to Hadoop and are migrating off of the architecture in large numbers. You will also learn how elastic compute models’ benefits help one customer scale their analytics and AI workloads and best practices from their experience on a successful migration of their data and workloads to the cloud.
Data-Ed Slides: Best Practices in Data Stewardship (Technical)DATAVERSITY
In order to find value in your organization's data assets, heroic data stewards are tasked with saving the day- every single day! These heroes adhere to a data governance framework and work to ensure that data is: captured right the first time, validated through automated means, and integrated into business processes. Whether its data profiling or in depth root cause analysis, data stewards can be counted on to ensure the organization's mission critical data is reliable. In this webinar we will approach this framework, and punctuate important facets of a data steward’s role.
Learning Objectives:
- Understand the business need for a data governance framework
- Learn why embedded data quality principles are an important part of system/process design
- Identify opportunities to help drive your organization to a data driven culture
Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Data Modeling, Data Governance, & Data QualityDATAVERSITY
Data Governance is often referred to as the people, processes, and policies around data and information, and these aspects are critical to the success of any data governance implementation. But just as critical is the technical infrastructure that supports the diverse data environments that run the business. Data models can be the critical link between business definitions and rules and the technical data systems that support them. Without the valuable metadata these models provide, data governance often lacks the “teeth” to be applied in operational and reporting systems.
Join Donna Burbank and her guest, Nigel Turner, as they discuss how data models & metadata-driven data governance can be applied in your organization in order to achieve improved data quality.
How to Build & Sustain a Data Governance Operating Model DATUM LLC
Learn how to execute a data governance strategy through creation of a successful business case and operating model.
Originally presented to an audience of 400+ at the Master Data Management & Data Governance Summit.
Visit www.datumstrategy.com for more!
Straight Talk to Demystify Data LineageDATAVERSITY
Are you sure you trust the data you just used for that $10 million decision? To trust data authenticity we must first understand its lineage. However, the term "Data Lineage" itself is ambiguous since it is used in different contexts. "Business Lineage" links metadata constructs to specific terms in a business glossary. This approach is used by numerous Data Governance solutions. This approach alone comes up short, since it doesn't trace the real flow of information through an organization. "Technical Lineage" traces data's journey through different systems and data stores, providing an audit trail of the changes along the way. True "Data Lineage" combines both aspects, providing context to fully understand the data life cycle. Every step in data's journey is a potential source for introduction of error that could compromise Data Quality, and hence, business decisions. In this session, Ron Huizenga offers a comprehensive discussion of data lineage and associated Data Quality remediation approaches that are essential to build a foundation for Data Governance.
Data Architecture - The Foundation for Enterprise Architecture and GovernanceDATAVERSITY
Organizations are faced with an increasingly complex data landscape, finding themselves unable to cope with exponentially increasing data volumes, compounded by additional regulatory requirements with increased fines for non-compliance. Enterprise architecture and data governance are often discussed at length, but often with different stakeholder audiences. This can result in complementary and sometimes conflicting initiatives rather than a focused, integrated approach. Data governance requires a solid data architecture foundation in order to support the pillars of enterprise architecture. In this session, IDERA’s Ron Huizenga will discuss a practical, integrated approach to effectively understand, define and implement an cohesive enterprise architecture and data governance discipline with integrated modeling and metadata management.
The Persona-Based Value of Modern Data Governance Precisely
Yes, data governance solutions are now a business imperative. But modern demands are requiring integrated capabilities to discover, understand, profile, and measure data integrity across many different functions across your organization.
This presentation shares four persona-based use cases & demos to illustrate how a single modular, and interoperable solution can optimize collaboration and empower your data teams to deliver data-driven decisions faster and more confidently.
Are you ready for the future of data governance? Check out what will be required:
• Understand data relationships to business objectives, metrics, and request new actions
• Discover new data element alerts to profile and add contextual details to your analysis
• Review needed data quality rules, lineage, and impact and proactively
monitor data changes over time.
• Access & respond to data replication request for more timely results
• Create data quality pipelines and enrich data for more insightful analytics
Master data management (mdm) & plm in context of enterprise product managementTata Consultancy Services
The presentation discusses the classical features and advantages of Master Data Management (MDM) system along with appropriate situations to use it. How do companies apply MDM who design, manufacture and sell their products in several geographies facing challenges in making appropriate decisions on their investment in PLM & MDM space?
Another important aspect covers the comparison/relation between a MDM system (or Product Master System) and Enterprise PLM system. How can you maximize your ROI on both PLM and MDM investments? With examples from different industries the key takeaways include whether your organization requires an MDM solution or not.
Best Practices in DataOps: How to Create Agile, Automated Data PipelinesEric Kavanagh
Synthesis Webcast with Eric Kavanagh and Tamr
DataOps is an emerging set of practices, processes, and technologies for building and automating data pipelines to meet business needs quickly. As these pipelines become more complex and development teams grow in size, organizations need better collaboration and development processes to govern the flow of data and code from one step of the data lifecycle to the next – from data ingestion and transformation to analysis and reporting.
DataOps is not something that can be implemented all at once or in a short period of time. DataOps is a journey that requires a cultural shift. DataOps teams continuously search for new ways to cut waste, streamline steps, automate processes, increase output, and get it right the first time. The goal is to increase agility and cycle times, while reducing data defects, giving developers and business users greater confidence in data analytic output.
This webcast examines how organizations adopt DataOps practices in the field. It will review results of an Eckerson Group survey that sheds light on the rate and scope of DataOps adoption. It will also describe case studies of organizations that have successfully implemented DataOps practices, the challenges they have encountered and benefits they’ve received.
Tune into our webcast to learn:
- User perceptions of DataOps
- The rate of DataOps adoption by industry and other demographic variables
- DataOps adoption by technique and component (i.e., agile, test automation, orchestration, continuous development/continuous integration)
- Key challenges organizations face with DataOps
- Key benefits organizations experience with DataOps
- Best practices in doing DataOps
- Case studies and anecdotes of DataOps at companies
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Data Profiling, Data Catalogs and Metadata HarmonisationAlan McSweeney
These notes discuss the related topics of Data Profiling, Data Catalogs and Metadata Harmonisation. It describes a detailed structure for data profiling activities. It identifies various open source and commercial tools and data profiling algorithms. Data profiling is a necessary pre-requisite activity in order to construct a data catalog. A data catalog makes an organisation’s data more discoverable. The data collected during data profiling forms the metadata contained in the data catalog. This assists with ensuring data quality. It is also a necessary activity for Master Data Management initiatives. These notes describe a metadata structure and provide details on metadata standards and sources.
Data Mesh in Practice - How Europe's Leading Online Platform for Fashion Goes...Dr. Arif Wider
A talk presented by Max Schultze from Zalando and Arif Wider from ThoughtWorks at NDC Oslo 2020.
Abstract:
The Data Lake paradigm is often considered the scalable successor of the more curated Data Warehouse approach when it comes to democratization of data. However, many who went out to build a centralized Data Lake came out with a data swamp of unclear responsibilities, a lack of data ownership, and sub-par data availability.
At Zalando - europe’s biggest online fashion retailer - we realised that accessibility and availability at scale can only be guaranteed when moving more responsibilities to those who pick up the data and have the respective domain knowledge - the data owners - while keeping only data governance and metadata information central. Such a decentralized and domain focused approach has recently been coined a Data Mesh.
The Data Mesh paradigm promotes the concept of Data Products which go beyond sharing of files and towards guarantees of quality and acknowledgement of data ownership.
This talk will take you on a journey of how we went from a centralized Data Lake to embrace a distributed Data Mesh architecture and will outline the ongoing efforts to make creation of data products as simple as applying a template.
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. I’ll include use cases so you can see what approach will work best for your big data needs.
If you’re in the business of collecting and analyzing data, you know that it’s vital to have the
right tools to do so. The Qlik Cloud® gives you everything you need to collect, manage, and
analyze your data. It’s the only platform that brings together all your data and analytics.
Whether you’re a large enterprise or a small business, you’ll nd the Qlik Cloud® to be the
perfect solution for your needs.
Data Modeling, Data Governance, & Data QualityDATAVERSITY
Data Governance is often referred to as the people, processes, and policies around data and information, and these aspects are critical to the success of any data governance implementation. But just as critical is the technical infrastructure that supports the diverse data environments that run the business. Data models can be the critical link between business definitions and rules and the technical data systems that support them. Without the valuable metadata these models provide, data governance often lacks the “teeth” to be applied in operational and reporting systems.
Join Donna Burbank and her guest, Nigel Turner, as they discuss how data models & metadata-driven data governance can be applied in your organization in order to achieve improved data quality.
How to Build & Sustain a Data Governance Operating Model DATUM LLC
Learn how to execute a data governance strategy through creation of a successful business case and operating model.
Originally presented to an audience of 400+ at the Master Data Management & Data Governance Summit.
Visit www.datumstrategy.com for more!
Straight Talk to Demystify Data LineageDATAVERSITY
Are you sure you trust the data you just used for that $10 million decision? To trust data authenticity we must first understand its lineage. However, the term "Data Lineage" itself is ambiguous since it is used in different contexts. "Business Lineage" links metadata constructs to specific terms in a business glossary. This approach is used by numerous Data Governance solutions. This approach alone comes up short, since it doesn't trace the real flow of information through an organization. "Technical Lineage" traces data's journey through different systems and data stores, providing an audit trail of the changes along the way. True "Data Lineage" combines both aspects, providing context to fully understand the data life cycle. Every step in data's journey is a potential source for introduction of error that could compromise Data Quality, and hence, business decisions. In this session, Ron Huizenga offers a comprehensive discussion of data lineage and associated Data Quality remediation approaches that are essential to build a foundation for Data Governance.
Data Architecture - The Foundation for Enterprise Architecture and GovernanceDATAVERSITY
Organizations are faced with an increasingly complex data landscape, finding themselves unable to cope with exponentially increasing data volumes, compounded by additional regulatory requirements with increased fines for non-compliance. Enterprise architecture and data governance are often discussed at length, but often with different stakeholder audiences. This can result in complementary and sometimes conflicting initiatives rather than a focused, integrated approach. Data governance requires a solid data architecture foundation in order to support the pillars of enterprise architecture. In this session, IDERA’s Ron Huizenga will discuss a practical, integrated approach to effectively understand, define and implement an cohesive enterprise architecture and data governance discipline with integrated modeling and metadata management.
The Persona-Based Value of Modern Data Governance Precisely
Yes, data governance solutions are now a business imperative. But modern demands are requiring integrated capabilities to discover, understand, profile, and measure data integrity across many different functions across your organization.
This presentation shares four persona-based use cases & demos to illustrate how a single modular, and interoperable solution can optimize collaboration and empower your data teams to deliver data-driven decisions faster and more confidently.
Are you ready for the future of data governance? Check out what will be required:
• Understand data relationships to business objectives, metrics, and request new actions
• Discover new data element alerts to profile and add contextual details to your analysis
• Review needed data quality rules, lineage, and impact and proactively
monitor data changes over time.
• Access & respond to data replication request for more timely results
• Create data quality pipelines and enrich data for more insightful analytics
Master data management (mdm) & plm in context of enterprise product managementTata Consultancy Services
The presentation discusses the classical features and advantages of Master Data Management (MDM) system along with appropriate situations to use it. How do companies apply MDM who design, manufacture and sell their products in several geographies facing challenges in making appropriate decisions on their investment in PLM & MDM space?
Another important aspect covers the comparison/relation between a MDM system (or Product Master System) and Enterprise PLM system. How can you maximize your ROI on both PLM and MDM investments? With examples from different industries the key takeaways include whether your organization requires an MDM solution or not.
Best Practices in DataOps: How to Create Agile, Automated Data PipelinesEric Kavanagh
Synthesis Webcast with Eric Kavanagh and Tamr
DataOps is an emerging set of practices, processes, and technologies for building and automating data pipelines to meet business needs quickly. As these pipelines become more complex and development teams grow in size, organizations need better collaboration and development processes to govern the flow of data and code from one step of the data lifecycle to the next – from data ingestion and transformation to analysis and reporting.
DataOps is not something that can be implemented all at once or in a short period of time. DataOps is a journey that requires a cultural shift. DataOps teams continuously search for new ways to cut waste, streamline steps, automate processes, increase output, and get it right the first time. The goal is to increase agility and cycle times, while reducing data defects, giving developers and business users greater confidence in data analytic output.
This webcast examines how organizations adopt DataOps practices in the field. It will review results of an Eckerson Group survey that sheds light on the rate and scope of DataOps adoption. It will also describe case studies of organizations that have successfully implemented DataOps practices, the challenges they have encountered and benefits they’ve received.
Tune into our webcast to learn:
- User perceptions of DataOps
- The rate of DataOps adoption by industry and other demographic variables
- DataOps adoption by technique and component (i.e., agile, test automation, orchestration, continuous development/continuous integration)
- Key challenges organizations face with DataOps
- Key benefits organizations experience with DataOps
- Best practices in doing DataOps
- Case studies and anecdotes of DataOps at companies
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Data Profiling, Data Catalogs and Metadata HarmonisationAlan McSweeney
These notes discuss the related topics of Data Profiling, Data Catalogs and Metadata Harmonisation. It describes a detailed structure for data profiling activities. It identifies various open source and commercial tools and data profiling algorithms. Data profiling is a necessary pre-requisite activity in order to construct a data catalog. A data catalog makes an organisation’s data more discoverable. The data collected during data profiling forms the metadata contained in the data catalog. This assists with ensuring data quality. It is also a necessary activity for Master Data Management initiatives. These notes describe a metadata structure and provide details on metadata standards and sources.
Data Mesh in Practice - How Europe's Leading Online Platform for Fashion Goes...Dr. Arif Wider
A talk presented by Max Schultze from Zalando and Arif Wider from ThoughtWorks at NDC Oslo 2020.
Abstract:
The Data Lake paradigm is often considered the scalable successor of the more curated Data Warehouse approach when it comes to democratization of data. However, many who went out to build a centralized Data Lake came out with a data swamp of unclear responsibilities, a lack of data ownership, and sub-par data availability.
At Zalando - europe’s biggest online fashion retailer - we realised that accessibility and availability at scale can only be guaranteed when moving more responsibilities to those who pick up the data and have the respective domain knowledge - the data owners - while keeping only data governance and metadata information central. Such a decentralized and domain focused approach has recently been coined a Data Mesh.
The Data Mesh paradigm promotes the concept of Data Products which go beyond sharing of files and towards guarantees of quality and acknowledgement of data ownership.
This talk will take you on a journey of how we went from a centralized Data Lake to embrace a distributed Data Mesh architecture and will outline the ongoing efforts to make creation of data products as simple as applying a template.
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. I’ll include use cases so you can see what approach will work best for your big data needs.
If you’re in the business of collecting and analyzing data, you know that it’s vital to have the
right tools to do so. The Qlik Cloud® gives you everything you need to collect, manage, and
analyze your data. It’s the only platform that brings together all your data and analytics.
Whether you’re a large enterprise or a small business, you’ll nd the Qlik Cloud® to be the
perfect solution for your needs.
Qlik Advanced Training helps in making the visual dashboard creation very easy and intuitive, but it does not limit itself there. It further goes on making everything simpler to find out the data, so that you will have an idea of what is going on and why.
Según Business Insider, IoT puede definirse como “una red de objetos conectados a Internet capaces de recopilar e intercambiar datos utilizando sensores incorporados". Esto puede aplicarse a muchos casos de uso, como contadores inteligentes, demandas de los consumidores, gestión de flotas, vehículos conectados, monitoreo remoto de pacientes, gestión de inventario automatizada, producción, mantenimiento predictivo y muchas otras áreas.
IBM & Cloudera: Hybrid Cloud & the Power of Possibilitiesomkar_nimbalkar
Joint Keynote Session by Omkar Nimbalkar (VP, WW Hybrid Cloud Build Team at IBM) and Nadeem Asghar (VP Partner/Sales Engineering & Global Field CTO at Cloudera) at the Chief Data & Analytics Officer (CDAO) Fall Virtual Summit on Wednesday, October 13, 2021.
Each and every business is unique. From healthcare to retail, manufacturing or finance — no two businesses
operate the same way. That’s why the Microsoft Cloud can be tailored to meet the needs of any enterprise.
It’s the cloud that helps drive unparalleled productivity. The cloud that turns massive streams of data into
actionable insight. The cloud that scales rapidly t o meet the growing demands of your business. And the
cloud that transforms a mobile workforce into a connected team. This is the cloud that’s built for your business.
A análise visual com o Qlik Sense® Cloud torna fácil desvendar insights de negócios valiosos. Aprenda os conceitos básicos e obtenha as respostas que você precisa, agora mesmo.
Com o Qlik Sense® Cloud, não há downloads, problemas ou truques – apenas insights confiáveis para a sua empresa. Ele está pronto agora, a um preço acessível. Neste SlideShare, dividimos os conceitos básicos do Qlik Sense Cloud, incluindo o seu modelo associativo exclusivo, a facilidade de colaboração e as visualizações convincentes e interativas que ajudam você a contar histórias persuasivas. Descubra como obter as respostas que sua empresa precisa, agora mesmo.
Les analyses visuelles de Qlik Sense® Cloud vous permettent d'accéder facilement à des informations commerciales précieuses. Découvrez les bases et obtenez immédiatement les réponses que vous recherchez.
Qlik Sense® Cloud ne nécessite pas de téléchargements et ne s'accompagne d'aucune complication ou obligation d'achat. Cette solution, prête instantanément à un prix abordable, permet à votre entreprise de disposer d'informations fiables. Ce SlideShare présente les bases de Qlik Sense Cloud, y compris son modèle associatif unique, la simplicité de collaboration et les visualisations attrayantes et interactives qui vous permettent de raconter des histoires convaincantes. Découvrez comment extraire dès maintenant les réponses nécessaires à votre activité.
Visuell dataanalys med Qlik Sense® Cloud gör det enkelt att få värdefull affärsinformation. Lär dig grunderna och få svaren du behöver. Nu.
Qlik Sense® Cloud har inga nedladdningar, inget trassel och ingen hake – bara tillförlitlig information för ditt företag. Och du kan börja använda det nu, till ett pris du har råd med. I denna SlideShare tar vi upp grunderna i Qlik Sense Cloud, bland annat vår unika associativa modell, hur enkelt det är att samverka med andra och hur tilltalande interaktiva visualiseringar hjälper dig att berätta övertygande historier. Ta reda på hur du får svaren ditt företag behöver. Nu.
Sju tecken på att du har växt ur Excel (Och vad du bör göra åt det)Qlik
Behöver ditt företag mer information än Excel kan ge dig? Läs mer om hur molnbaserad dataanalys synliggör dolda samband i dina data, utan fördröjning.
Kalkylblad är toppen, men de har sina begränsningar. Oavsett hur stort eller litet ditt företag är når du en punkt när du vill ha mer ingående och avancerad information – som kan förändra verksamheten i grunden. I denna SlideShare får du lära dig hur molnbaserad dataanalys kan lösa dina kalkylbladsproblem och hjälpa dig nå konkreta, datadrivna insikter direkt.
5 Ways to Improve Sales Performance with AnalyticsQlik
In this e-book, we'll look at some trends in the use of analytics by sales—including what's working and what's not—then look at 5 ways to improve sales performance with analytics.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
2. 2
Now more than ever, data is the key to business success. And thanks to
cloud analytics, any business can get world-class, data-driven insights.
In this piece, we cover some of the benefits of Qlik’s leading cloud
analytics offering, Qlik Sense Cloud.
Get insights from your data right now, without setup and
installation hassles
Freely explore associations with just a few clicks
Find patterns and tell stories with clear, interactive data visualizations
Collaborate and share easily with team members
3. 3
Start Online, Stay Online
Visit qlik.com/cloud to create your account and get started for free.
Qlik Sense Cloud does all the setup for you – no downloads, no installations,
and no infrastructure to maintain. Everything is automatically up-to-date,
meaning you can focus your efforts on gaining fast, reliable insights and
making smart business decisions.
4. 4
Once you have an account, you can access and start exploring
your data right away – anywhere, from any device.
Qlik Sense Cloud is a fully web-based experience. You can
store your data and apps, access resources, and share your
apps with others – all from a highly secure cloud environment.
5. 5
Import and Associate Your Data
Qlik Sense Cloud enables you to quickly import multiple sets of data to a
centralized location for use in any of your data analysis. You can even add
external data — like population and weather — to layer in more context and
gain even deeper insights.
And with Qlik’s associative model you can probe all the possible connections
in all your data — so you can spot the hidden connections that other solutions
miss. Freely explore complex information and answer the tough “why”
questions. No predefined questions or data hierarchies get in your way.
5
CUSTOMERS PRODUCTS
SALES
6. Qlik Sense Cloud evaluates the data for you and provides recommendations for
the best associations among your data sets – no technical expertise required.
Connect and associate multiple sets
of data by pulling “bubbles” together.
Understand the associations being
made and adjust them if needed.
6
7. 7
Create Visualizations
Effective visualizations allow you to see patterns and tell engaging stories with
your data. But pretty charts aren’t enough to gain deep insights. Qlik’s powerful
associative model underpins smart, interactive visualizations, empowering you to
explore the full scope of your data – regardless of its size or structure – so you
can make smarter business decisions.
CUSTOMERS
PRODUCTS
SALES
8. 8
Qlik’s self-service data visualizations let you quickly uncover insights across multiple
data sources. Simply select the type of visualization, then adjust the dimensions
and measures, so you can create interactive visualizations in seconds.
9. Qlik’s associative engine dynamically recognizes and highlights associations – so
you can freely explore all the possibilities in your data. Charts, graphs, and other
visualizations will automatically interact with each other as Qlik Sense Cloud
calculates analytics in real time. And visualizations immediately update when you
make selections, helping you uncover patterns and connections right away.
9
10. Share Your Insights
Your data and visualizations are readily accessible by anyone on your team,
so collaboration is easier than ever. With the tap of a button, you can share
visualizations and insights – both inside and outside of your organization –
amplifying the value of data and accelerating decision making.
10
11. 11
Ready to get started?
Log in to Qlik Sense Cloud now to start uncovering valuable
insights you need to drive your business forward.
Try Qlik Sense Cloud for free –
and get the answers your business needs.
qlik.com/cloud
Know. Right now.
If you’re interested in more
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