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This Data Warehouse Tutorial For Beginners will give you an introduction to data warehousing and business intelligence. You will be able to understand basic data warehouse concepts with examples. The following topics have been covered in this tutorial:
1. What Is The Need For BI?
2. What Is Data Warehousing?
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a. OLTP Vs OLAP
b. ETL
c. Data Mart
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4. Data Warehouse Architecture
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BI Consultancy - Data, Analytics and StrategyShivam Dhawan
The presentation describes my views around the data we encounter in digital businesses like:
- Looking at common Data collection methodologies,
-What are the common issues within the decision support system and optimiztion lifecycle,
- Where are most of failing?
and most importantly, "How to connect the dots and move from Data to Strategy?"
I work with all facets of Web Analytics and Business Strategy and see the structures and governance models of various domains to establish and analyze the key performance indicators that allow you to have a 360º overview of online and offline multi-channel environment.
Apart from my experience with the leading analytic tools in the market like Google Analytics, Omniture and BI tools for Big Data, I am developing new solutions to solve complex digital / business problems.
As a resourceful consultant, I can connect with your team in any modality or in any form that meets your needs and solves any data/strategy problem.
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Based on the analysis of Digital Transformation and Values Transformation, Forrester gives its insight and orientations in terms of Data Governance 2.0 and Data Citizenship.
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Learn about the business demands driving modernization, the benefits of doing so, and how to get started.
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This Data Warehouse Tutorial For Beginners will give you an introduction to data warehousing and business intelligence. You will be able to understand basic data warehouse concepts with examples. The following topics have been covered in this tutorial:
1. What Is The Need For BI?
2. What Is Data Warehousing?
3. Key Terminologies Related To Data Warehouse Architecture:
a. OLTP Vs OLAP
b. ETL
c. Data Mart
d. Metadata
4. Data Warehouse Architecture
5. Demo: Creating A Data Warehouse
BI Consultancy - Data, Analytics and StrategyShivam Dhawan
The presentation describes my views around the data we encounter in digital businesses like:
- Looking at common Data collection methodologies,
-What are the common issues within the decision support system and optimiztion lifecycle,
- Where are most of failing?
and most importantly, "How to connect the dots and move from Data to Strategy?"
I work with all facets of Web Analytics and Business Strategy and see the structures and governance models of various domains to establish and analyze the key performance indicators that allow you to have a 360º overview of online and offline multi-channel environment.
Apart from my experience with the leading analytic tools in the market like Google Analytics, Omniture and BI tools for Big Data, I am developing new solutions to solve complex digital / business problems.
As a resourceful consultant, I can connect with your team in any modality or in any form that meets your needs and solves any data/strategy problem.
Data product thinking-Will the Data Mesh save us from analytics historyRogier Werschkull
Data Mesh: What is it, for Who, for who definitely not?
What are it's foundational principles and how could we take some of them to our current Data Analytical Architectures?
Data Lakehouse, Data Mesh, and Data Fabric (r2)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 modern data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. They all may sound great in theory, but I'll dig into the concerns you need to be aware of before taking the plunge. I’ll also include use cases so you can see what approach will work best for your big data needs. And I'll discuss Microsoft version of the data mesh.
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Watch this webinar to learn about the benefits of using semantic and graph database technology to create a Data Catalog of all of an enterprise's data, regardless of source or format, as part of a modern IT or data management stack and an important step toward building an Enterprise Data Fabric.
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How you can gain rapid insights and create more flexibility by capturing and storing data from a variety of sources and structures into a NoSQL database.
The Path to Data and Analytics ModernizationAnalytics8
Learn about the business demands driving modernization, the benefits of doing so, and how to get started.
Can your data and analytics solutions handle today’s challenges?
To stay competitive in today’s market, companies must be able to use their data to make better decisions. However, we are living in a world flooded by data, new technologies, and demands from the business for better and more advanced analytics. Most companies do not have the modern technologies and processes in place to keep up with these growing demands. They need to modernize how they collect, analyze, use, and share their data.
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We cover:
-The business demands and industry shifts that are impacting the need to modernize
-The benefits of data and analytics modernization
-How to approach data and analytics modernization- steps you need to take and how to get it right
-The pillars of modern data management
-Tips for migrating from legacy analytics tools to modern, next-gen platforms
-Lessons learned from companies that have gone through the modernization process
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I've shown you in this ppt, the difference between Data and Big Data. How Big Data is generated, Opportunities with Big Data, Problem occurred in Big Data, solution of that problem, Big Data tools, What is Data Science & how it's related with the Big Data, Data Scientist vs Data Analyst. At last, one Real-life scenario where Big data, data scientists, and data analysts work together.
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DOI: 10.13140/RG.2.2.10638.36162
Data stewards are the implementation arm of Data Governance. They are also the first line of defense against bad data practices. Whether it’s data profiling or in-depth root cause analysis, data stewards ensure the organization’s shared data is reliably interconnected. Whether starting or restarting your Data Stewardship program, success comes from:
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- Proving value with tangible ROI
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Big Data Ppt PowerPoint Presentation Slides SlideTeam
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This workshop presentation from Enterprise Knowledge team members Joe Hilger, Founder and COO, and Sara Nash, Technical Analyst, was delivered on June 8, 2020 as part of the Data Summit 2020 virtual conference. The 3-hour workshop provided an interdisciplinary group of participants with a definition of what a knowledge graph is, how it is implemented, and how it can be used to increase the value of your organization’s datas. This slide deck gives an overview of the KM concepts that are necessary for the implementation of knowledge graphs as a foundation for Enterprise Artificial Intelligence (AI). Hilger and Nash also outlined four use cases for knowledge graphs, including recommendation engines and natural language query on structured data.
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With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
I've shown you in this ppt, the difference between Data and Big Data. How Big Data is generated, Opportunities with Big Data, Problem occurred in Big Data, solution of that problem, Big Data tools, What is Data Science & how it's related with the Big Data, Data Scientist vs Data Analyst. At last, one Real-life scenario where Big data, data scientists, and data analysts work together.
Big Data & Analytics (Conceptual and Practical Introduction)Yaman Hajja, Ph.D.
A 3-day interactive workshop for startups involve in Big Data & Analytics in Asia. Introduction to Big Data & Analytics concepts, and case studies in R Programming, Excel, Web APIs, and many more.
DOI: 10.13140/RG.2.2.10638.36162
Data stewards are the implementation arm of Data Governance. They are also the first line of defense against bad data practices. Whether it’s data profiling or in-depth root cause analysis, data stewards ensure the organization’s shared data is reliably interconnected. Whether starting or restarting your Data Stewardship program, success comes from:
- Understanding the cadence/role of foundational data practices supporting organizational operations
- Proving value with tangible ROI
- Improving effectiveness/efficiencies using organization-wide insight
- Comprehending how stewards need to be multifunctional and dexterous, especially at first
- Integrating the role of data debt fighting
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how data architecture is a key component of an overall enterprise architecture for enhanced business value and success.
Databricks is a Software-as-a-Service-like experience (or Spark-as-a-service) that is a tool for curating and processing massive amounts of data and developing, training and deploying models on that data, and managing the whole workflow process throughout the project. It is for those who are comfortable with Apache Spark as it is 100% based on Spark and is extensible with support for Scala, Java, R, and Python alongside Spark SQL, GraphX, Streaming and Machine Learning Library (Mllib). It has built-in integration with many data sources, has a workflow scheduler, allows for real-time workspace collaboration, and has performance improvements over traditional Apache Spark.
At wetter.com we build analytical B2B data products and heavily use Spark and AWS technologies for data processing and analytics. I explain why we moved from AWS EMR to Databricks and Delta and share our experiences from different angles like architecture, application logic and user experience. We will look how security, cluster configuration, resource consumption and workflow changed by using Databricks clusters as well as how using Delta tables simplified our application logic and data operations.
Big Data Ppt PowerPoint Presentation Slides SlideTeam
Big data has brought about a revolution in the field of information technology. Our content-ready big data PPT PowerPoint presentation slides shed light on the importance and relevance of large volumes of data. The data management presentation covers myriad of topics such as big data sources, market forecast, 3 Vs, technologies, workflow, data analytics process, impact, benefit, future, opportunity and challenges, and many additional slides containing graphs and charts. The biggest benefit that this big data analytics presentation template offers is that it enables you to unearth the information that can be used to shape the future of your business. Moreover, these designs can also be utilized to craft your own presentation on predictive analytics, data processing application, database, cloud computing, business intelligence, and user behavior analytics. Download big data PPT visuals which will help you make accurate business decisions. Enlighten folks on fraud with our Big Data PPt PowerPoint Presentation Slides. Convince them to be highly alert.
Business Intelligence made easy! This is the first part of a two-part presentation I prepared for one of our customers to help them understand what Business Intelligence is and what can it do...
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
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Unlocking Value of Data in a Digital AgeRuud Brink
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89% of consumers switch to a competitor after a poor CX Abhishek Sood
89% of consumers switch to a competitor following a poor customer experience, according to an Oracle study. But how can you use digital technology to improve your customers' experience?
Uncover how several prominent businesses embraced digital technologies to retain customers and increase profits. For example, Domino's Pizza had a 23% growth in profit after it allowed customers to track their deliveries online.
Discover the 4 factors that can make a digital transformation project profitable and worthwhile.
The Digital Enterprise Vol 5 - A Framework for TransformationStuart Lamb
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Digital Transformation in Manufacturing - A Whitepaper by RapidValue SolutionsRapidValue
This whitepaper aims to answer some of the common questions around digital transformation specifically for the business leaders in the manufacturing industry. Because of the role that technology plays today in a organization's ability to evolve, business leaders must lead their organizations through this era of digital transformation.
The survival kit for your digital transformationrun_frictionless
To go digital, you need an IT organization, an enterprise architecture, IT processes, and tools that allow for new projects to go live tomorrow instead of next week. The ability to do this will give you a competitive advantage and it will also reduce costs. But how do you get there? This white paper will get you there.
https://runfrictionless.com/b2b-white-paper-service/
Κεντρική Ομιλία: Κωστής Χλουβεράκης, Επικεφαλής Γενικής Διεύθυνσης Digital Banking, Eurobank
Τίτλος Ομιλίας: «Καινοτομία στην σημερινή Τράπεζα: Προκλήσεις, Τάσεις και Προοπτικές»
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𝐓𝐉 𝐂𝐨𝐦𝐬 provides unlimited package services including such as Event organizing, Event planning, Event production, Manpower, PR marketing, Design 2D/3D, VIP protocols, Interpreter agency, etc.
Sports events - Golf competitions/billiards competitions/company sports events: dynamic and challenging
⭐ 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐝 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬:
➢ 2024 BAEKHYUN [Lonsdaleite] IN HO CHI MINH
➢ SUPER JUNIOR-L.S.S. THE SHOW : Th3ee Guys in HO CHI MINH
➢FreenBecky 1st Fan Meeting in Vietnam
➢CHILDREN ART EXHIBITION 2024: BEYOND BARRIERS
➢ WOW K-Music Festival 2023
➢ Winner [CROSS] Tour in HCM
➢ Super Show 9 in HCM with Super Junior
➢ HCMC - Gyeongsangbuk-do Culture and Tourism Festival
➢ Korean Vietnam Partnership - Fair with LG
➢ Korean President visits Samsung Electronics R&D Center
➢ Vietnam Food Expo with Lotte Wellfood
"𝐄𝐯𝐞𝐫𝐲 𝐞𝐯𝐞𝐧𝐭 𝐢𝐬 𝐚 𝐬𝐭𝐨𝐫𝐲, 𝐚 𝐬𝐩𝐞𝐜𝐢𝐚𝐥 𝐣𝐨𝐮𝐫𝐧𝐞𝐲. 𝐖𝐞 𝐚𝐥𝐰𝐚𝐲𝐬 𝐛𝐞𝐥𝐢𝐞𝐯𝐞 𝐭𝐡𝐚𝐭 𝐬𝐡𝐨𝐫𝐭𝐥𝐲 𝐲𝐨𝐮 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐚 𝐩𝐚𝐫𝐭 𝐨𝐟 𝐨𝐮𝐫 𝐬𝐭𝐨𝐫𝐢𝐞𝐬."
What are the main advantages of using HR recruiter services.pdfHumanResourceDimensi1
HR recruiter services offer top talents to companies according to their specific needs. They handle all recruitment tasks from job posting to onboarding and help companies concentrate on their business growth. With their expertise and years of experience, they streamline the hiring process and save time and resources for the company.
3. What is Digital Transformation?
Digital transformation is the profound and accelerating transformation
of business activities, processes, competencies and models to fully
leverage the changes and opportunities of digital technologies and
their impact in a strategic and prioritized way.
3
Digital Transformation is NOT…
• Business Innovation
• Digital Experience
• Digital Strategy
TRUE DIGITAL TRANSFORMATION NEEDS TO INVOLVE MUCH MORE THAN JUST THE END PRODUCT
• Digital Disruption
• Disruptive Innovation
• Disruptive Technologies
http://www.i-scoop.eu/digital-transformation/
4. Digital Transformation: Make it More Relevant
• Social, mobile, and real-time technologies
have transformed people’s lives—and
their expectations for how they interact
with organizations.
• As part of that evolution, organizations
need to transform to meet these new
expectations with every connection.
• We think of digital transformation as the
alignment of businesses to their
customers at every touchpoint in their
customer journey.
5. What is Digital Transformation?
“The coupling of granular, real-time data (e.g., smartphones,
connected devices, smart appliances, wearables, mobile commerce,
video surveillance) with modern technologies (e.g., cloud native apps,
big data architectures, hyper-converged technologies, artificial
intelligence, blockchain) to enhance products, processes, and business-
decision making with customer, product and operational insights.”
5 https://www.cio.com/article/3199030/analytics/what-is-digital-transformation.html
8. Data Science and Digital Transformation
• By 2020, 60% of all enterprises will have fully articulated an
organization-wide digital platform strategy and will be in the process
of implementing that strategy as the new IT core for competing in the
digital economy.
• By 2021, spending on cloud services and cloud-enabling hardware,
software and services will more than double to over $530 billion,
leveraging the diversifying cloud environment that is 20% at the edge,
and over 90% multi-cloud.
• By 2021, enterprise apps will shift toward hyper-agile architectures,
with 80% of application development on cloud platforms (PaaS) using
microservices and cloud functions, and over 95% of new
microservices deployed in containers.
8 Microsoft
9. An article in
“Information Age”
magazine boldly
asserts that “data
science is the driving
force behind digital
transformation”!
9 http://www.information-age.com/data-science-driving-force-behind-successful-digital-transformation-123462527/
Data Science
and
Digital
Transformation
10. Data Science and Digital Transformation
•In the age of the customer, successful companies
maximize customer intelligence by turning big
data into actionable business insights.
•We define big data as the practices, processes,
and technologies that close the gap between
having the data available and having the ability
to turn it into business insights.
10 https://www.forrester.com/report/New+Evolving+Tools+To+Manage+Big+Data+Will+Grow+At+DoubleDigit+Rates/-/E-RES136366
11. Data Science and Digital Transformation
•Big data is bringing with it the ability to transform
industries and the potential to turn traditional, long-
standing business models on their head. For
businesses, the issue to be addressed is how to make
the most of all this data, turning it into actionable
insights.
•Help is at hand in the form of data science. The
analysis of patterns in the data allows organizations to
build models that create forecasts of what can happen
under different scenarios.
11 http://www.information-age.com/data-science-driving-force-behind-successful-digital-transformation-123462527/
12. Data Science and Digital Transformation
“Digital transformation is about the evolution of
business through data science. Estimates are that
by the year 2020, up to 50 billion devices will be
connected to the internet. Imagine this massive
river of data, as information is collected and
stored every second, twenty-four hours a day, 365
days a year. The scale is nearly
incomprehensible!”
12 http://www.esri.com/digital-transformation
13. Data Science and Digital Transformation
• Research shows that less than 1% of available data is actually
being used, and most of that for the detection and control of
unusual events—a home security system going off, or a
pump on an oil rig sounding an alarm.
• The unrealized potential for predictive maintenance and
asset- and operational optimization is only beginning to be
grasped.
• The same study suggests that the “Internet of Things,” driven
by accelerating sensor proliferation in more and more kinds
of manufactured objects, may have an economic potential
of more than $11 trillion per year by 2025.
13 http://www.esri.com/digital-transformation
14. CX IS THE BATTLEGROUND FOR
LOYALTY
+ 17%
Companies are investing billions in CX. And for good reason.
Companies that get CX right outperform their peers on a number of important dimensions, including:
+ 11%
CUSTOMER LOYALTY REVENUES
Source: Forrester Research, Inc., “Expectations vs. Experience: The Good, The Bad, The Opportunity”, 2016
15. Data Science and Customer Experience
• Customer experience has become the most important driving factor
of Digital Transformation. Companies like Amazon, Apple or Disney
have embraced the power of analytics to understand their customers
and provide unmatched customer experience.
• Consumers are no longer satisfied when they are treated as a group
of people but they expect hyper-personalized touchpoints. Advanced
analytics embedded in each interaction, transaction, and process is
driving the next wave of productivity and growth.
• Businesses are using advanced analytics like Artificial Intelligence,
Deep Learning, and NLP for various insights.
• Data Science is at the intersection of digital transformation and
customer experience!
15 https://www.datasciencecentral.com/profiles/blogs/the-role-of-analytics-in-digital-transformation
16. Data Science and Customer Experience
• Businesses are using advanced analytics like Artificial Intelligence,
Deep Learning, and NLP for various insights.
• Real-Time analytics helps to get the right products in front of the
people looking for them or offering the right promotions to the
people most likely to buy.
• Digital Marketing is hugely benefited by Analytics due customer
analytics, brand analytics, competition analytics and conversion
analytics.
• Making forward-looking proactive decisions is possible via
forecasting, optimization, predictive analytics and text mining.
• Data is the new oil, but it is crude, and cannot really be used unless it
is refined with analytics to bring the new gold nuggets.
16 https://www.datasciencecentral.com/profiles/blogs/the-role-of-analytics-in-digital-transformation
17. Who Does Data Science Help
•Manufacturing
•Retail
•Insurance
•Financial
•Health Care
•Vehicle Maintenance
•Product Life Cycle Management
17 https://www.cio.com/article/3249905/analytics/the-unexpected-benefits-of-data-analytics.html
18. How Does Data Science Help
•Acts as the pulse on current operations
•Long term benefit of short term losses
•Warranty issues that give way to new
solutions
•Variable errors uncovering hidden causes
•Redefining Customer Success
18 https://www.cio.com/article/3249905/analytics/the-unexpected-benefits-of-data-analytics.html