ExistBI case study of Informatica Training and Informatica Consulting for Costco. The engagement demonstrates Business Intelligence Services of an Authorized Informatica Training partner.
The ExistBI data migration services team enabled Costco employees to have confidence in Informatica ILM implementation.
Tableau Conference 2014: How One Agency Evolved from Vendor to Strategic PartnerSIGMA Marketing Insights
- SIGMA Marketing Insights evolved from being a vendor that provided exhaustive data discovery and static reporting to clients, to becoming a strategic partner that uses Tableau to provide faster, more accessible, and engaging insights. Tableau helped transform SIGMA's culture and capabilities by enabling interactive dashboards, visualizations, and self-service access to data. This strategic shift strengthened SIGMA's service of illuminating clients' marketing strategies and driving customer growth through data-powered execution.
Your AI and ML Projects Are Failing – Key Steps to Get Them Back on TrackPrecisely
With recent studies indicating that 80% of AI and machine learning projects are failing due to data quality related issues, it’s critical to think holistically about this fact. This is not a simple topic – issues in data quality can occur throughout from starting the project through to model implementation and usage.
View this webinar on-demand, where we start with four foundational data steps to get our AI and ML projects grounded and underway, specifically:
• Framing the business problem
• Identifying the “right” data to collect and work with
• Establishing baselines of data quality through data profiling and business rules
• Assessing fitness for purpose for training and evaluating the subsequent models and algorithms
Knowledge Matters Issue 15 - Technology at ConcernEllen Ward
Digital data gathering (DDG) has improved Concern Worldwide's monitoring and evaluation practices in several ways:
1) It provides instant access to accurate data in real-time, accelerating evidence-based decision making.
2) It improves data reliability through built-in error controls and removing manual data entry.
3) It reduces data loss through automatic uploading and GPS tracking of enumerators.
4) It facilitates centralized data management through a uniform system.
While DDG has benefits, technology does not solve all problems - data collection is just one step, and other M&E processes like indicators and analysis plans are still important. Concern is looking to expand DDG use for regular monitoring and introduce
This document discusses the importance of managing data effectively and having clean, accurate data. It notes that dirty or unmanaged data can become unreliable very quickly as errors accumulate. It provides examples of what constitutes dirty data like duplicates, missing or inaccurate information. The document recommends having processes and standards for entering data to maintain data quality. These include reconciling donations, using batch numbers, and regular audits to identify dirty data issues. The overall message is that non-profits must treat data as a valuable asset and implement strategies to organize, maintain and protect their data.
This document discusses how to build social intelligence in organizations by bringing social capabilities to business intelligence (BI) tools. It recommends focusing on business goals, decoupling data collection from analysis, defining ad-hoc cross-functional teams, tying analysis to decision-making, and empowering business users with self-service analytics and collaborative workspaces. Examples of how social BI can help sales, operations, projects and management are provided.
The search for new business ideas and new business models is hit-or-miss in most corporations
When good ideas do emerge, they’re often doomed because the company is organized to support one way of doing business and doesn’t have the processes or metrics to support a new one.
The presentation includes the introduction to the topic, the various dimensions of big data, its evolution from big data 1.0 to bid data 3.0 and its impact on various industries, uses as well as the challenges it faces. The concluding slide gives a brief on the future of big data.
"Simplify Your Analytics Strategy" by Narendra MulaniSai Sandeep MN
Companies can get stuck trying to analyze all possible analytics opportunities instead of focusing on what matters most to customers, stakeholders, and employees. This document provides steps to simplify an analytics strategy and generate useful insights. It recommends accelerating data through a hybrid data platform and emerging technologies. A path to insight is unique for each organization and involves various elements like goals, data types and sources. Simplifying an analytics strategy can provide managerial insights through discovery-based or hypothesis-based approaches depending on whether the problem or solution is known.
The document discusses how businesses can overcome complexity and confusion with analytics by pursuing a simpler path to insights. It recommends creating a hybrid data environment to accelerate data delivery and insights. Businesses should delegate analytic work to technologies like business intelligence, data discovery, analytics applications, and machine learning. Each company's path to insights is unique, so they can take either a problem-focused or discovery-based approach depending on their needs. Uncovering opportunities requires making data-driven decisions once insights are found.
How to Leverage Traditional Media for a Successful Omnichannel StrategyTinuiti
Today’s shoppers are changing and evolving — and with that, your omnichannel retail strategy should too. Shopping journeys now go through a variety of branded touchpoints, both digital and physical, and they are nowhere near linear shopping journeys. Retailers need to make sure to be agile and responsive to customer needs with branded touchpoints to ensure a consistent buying experience across channels, both online and offline. Tune into our webinar as our team of experts discuss how we were able to optimize in store coupon redemption, attribute in store revenue to proper digital channels, and properly retarget consumers for a cohesive customer experience for our client’s success.
This document provides an overview of Lyn Murnane's experience in knowledge management roles across multiple organizations. It includes brief summaries of KM implementation examples at Medibank Private, Telstra, and IDP Education. At Medibank Private, challenges included inconsistent information across systems. Changes involved user research, a new intranet, and named knowledge bases. Outcomes were reduced help desk calls and improved staff engagement. Measures tracked usage and call handling times. Telstra consolidated multiple systems into a new intranet tool. IDP Education developed a large knowledge base and community site to support international student advisors.
Procter & Gamble is a top consumer products company that relies on collaboration and innovation. They implemented several information systems to improve productivity, including Web 2.0, blogs, a custom search engine, and a Microsoft collaboration suite. Telepresence technology allows high-definition meetings over long distances, saving travel costs. While some tools faced inertia, overall the systems fostered collaboration, reduced costs, and helped execute P&G's business strategy of maintaining popular products and developing new ones through innovation.
Data is a key enabler of digital transformation and innovation. It fuels new digital processes and solutions. To benefit from data, organizations must first define and organize core master data and then acquire the right competencies to analyze and combine both structured and unstructured internal and external data. This will allow organizations to discover innovative solutions through a "data-lab" approach and trials. Ensuring high quality master and process data is also important to enable seamless experiences across systems.
Actionable Analytics - Solving Real World Problems With Big Data, Xerox Innov...Innovation Enterprise
Xerox presented on using big data and analytics to solve real-world problems. They discussed using transportation fare collection data to build models that infer passenger travel patterns and populate city dashboards. They also discussed working with educators to use student assessment data to provide real-time reports and recommendations to tailor instruction. Finally, they presented on using social media data and analytics to transform customer care services by identifying issues, engaging customers, and measuring engagement effectiveness.
Pitney Bowes provides multi-channel communication solutions to help local governments transform how they interact with citizens. This includes enabling the digitization and automation of outbound communications, capturing printing and mailing from remote locations, and tracking physical items throughout their delivery. Relay Hub allows governments to centralize printing and mailing, standardize documents, and give recipients more choice in how they receive communications across both physical and digital channels. This improves efficiency, reduces costs, and enhances the citizen experience.
This document outlines Fiona De Brabanter's presentation at the Google Analytics User Conference in Belgium. The presentation introduced digital analytics and explained how analyzing both qualitative and quantitative data through tools like Google Analytics can help businesses continually improve their online experiences and measure whether their digital efforts are achieving desired outcomes. Several experts would also be sharing best practices for using Google Analytics and key concepts in digital analytics.
The document summarizes an agenda for an email measurement conference. It includes sessions on using data and metrics to improve marketing, focusing beyond just clicks and opens. Speakers will discuss how to leverage more customer data and metrics to improve campaigns, segmentation, and ROI. The final session will provide a summary of the event. Attendees will learn how to better measure and take action on more customer data and metrics to improve marketing performance.
Similar to .conf Go 2023 - Data analysis as a routine (20)
.conf Go 2023 - Raiffeisen Bank InternationalSplunk
This document discusses standardizing security operations procedures (SOPs) to increase efficiency and automation. It recommends storing SOPs in a code repository for versioning and referencing them in workbooks which are lists of standard tasks to follow for investigations. The goal is to have investigation playbooks in the security orchestration, automation and response (SOAR) tool perform the predefined investigation steps from the workbooks to automate incident response. This helps analysts automate faster without wasting time by having standard, vendor-agnostic procedures.
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.conf Go 2023 presentation:
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We are honored to launch and host this event for our UiPath Polish Community, with the help of our partners - Proservartner!
We certainly hope we have managed to spike your interest in the subjects to be presented and the incredible networking opportunities at hand, too!
Check out our proposed agenda below 👇👇
08:30 ☕ Welcome coffee (30')
09:00 Opening note/ Intro to UiPath Community (10')
Cristina Vidu, Global Manager, Marketing Community @UiPath
Dawid Kot, Digital Transformation Lead @Proservartner
09:10 Cloud migration - Proservartner & DOVISTA case study (30')
Marcin Drozdowski, Automation CoE Manager @DOVISTA
Pawel Kamiński, RPA developer @DOVISTA
Mikolaj Zielinski, UiPath MVP, Senior Solutions Engineer @Proservartner
09:40 From bottlenecks to breakthroughs: Citizen Development in action (25')
Pawel Poplawski, Director, Improvement and Automation @McCormick & Company
Michał Cieślak, Senior Manager, Automation Programs @McCormick & Company
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Mikolaj Zielinski, UiPath MVP, Senior Solutions Engineer @Proservartner
10:35 ☕ Coffee Break (15')
10:50 Document Understanding with my RPA Companion (45')
Ewa Gruszka, Enterprise Sales Specialist, AI & ML @UiPath
11:35 Power up your Robots: GenAI and GPT in REFramework (45')
Krzysztof Karaszewski, Global RPA Product Manager
12:20 🍕 Lunch Break (1hr)
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Kamil Miśko, UiPath MVP, Senior RPA Developer @Zurich Insurance
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Thomasz Wierzbicki, Business Analyst @Office Samurai
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The Pains of Manual AppSec:
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Are you interested in learning about creating an attractive website? Here it is! Take part in the challenge that will broaden your knowledge about creating cool websites! Don't miss this opportunity, only in "Redesign Challenge"!
Hire a private investigator to get cell phone recordsHackersList
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You can do the same for your projects, and this presentation will show you how, with an emphasis on the unique challenges that come up when working with Dart and Flutter.
The session will provide a walkthrough of the steps involved in securing a first repository, and then what it takes to repeat that process across an organization with multiple repos. It will also look at the ongoing maintenance involved once scorecards have been implemented, and how aspects of that maintenance can be better automated to minimize toil.
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⦿ Why is patent quality important?
⦿ How to balance quality and budget
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.conf Go 2023 - Data analysis as a routine
1. Data analysis
as a routine
Co-evolution of information system and data
analysis development
2. INTERNAL
• Posti Group
• Posti was established in Finland in 1638 by Per
Brahe.
• Delivery and logistics company mainly in
Finland, Sweden and Baltics
• Almost 20.000 employees
• Visiting 3M house holds and organizations in
Finland every weekday.
• A huge decrease in mail volumes due to the
digitalization in our society and worldwide.
• Efficiency improvements are sought through
increased automation, supported by data
analytics.
• Me
• Working in Posti since 1996 with information
systems, mostly in development tasks.
• Experience in different business groups,
services, and customers including both
consumers and commercial / non-commercial
organizations.
• Education:
• M.Sc., major in Computer Science and first
minor in Psychology
• Doing post graduate studies about
analytics as a routine in information
systems development.
About Posti and me
3. INTERNAL
How to continuously
improve the matching
in our mail sorting process?
A concept of the co-evolution
regarding the development of
Information System and data analysis
Topics of the presentation
13.9.2023
3
4. INTERNAL
13.9.2023
4
Getting my Donald Duck
The view from the subscriber
Sending my
Donald Duck
The Donald Duck
”company”
Me
Reading my
Donald Duck with
a sandwich and
juice
Marcus Gustafsson
5. INTERNAL
13.9.2023
5
Getting my Donald Duck
What really happens
Sender,
for example,
a magazine
publisher
Printing
house or
mailer
Advance
information
of recipients
Machine
sorting
Delivery
Customer
service
Receicing
mail
Printing and
preliminary
sorting
Trasportation of
mail items to
Posti
Inspection of
incoming
items
Manual
sorting
Sender & mailer /
printing house
Posti
Mail recipient
Marcus Gustafsson
To whom and to what address is this
mail to be delivered?
Sorting Delivery
6. INTERNAL
13.9.2023
6
To whom and to what address? Matching gives
the answer
the fundamental capability in sorting
Matti Meikäläinen
Tuohikatu 49 C 20
28100 PORI
Matching
718910
~1 000 million
Matti Meikäläinen custno: 290189
c/o Sanni Meikäläinen PL 192, Tuohikatu 49 C 20
28100 PORI
Sorting
2371891
7. INTERNAL
Questions we are ask almost daily:
• How good are we?
• What problems (potential targets for
improvements) do we have?
• What is the expected benefit of solving a problem?
• What part of the problem can be solved in a
cost-efficient way (80/20)?
• What do our customers prefer?
13.9.2023
7
How to improve matching?
Answers to questions can be found by
analyzing the production data
continuously
8. INTERNAL
13.9.2023
8
How do we do analytics?
Inspection
Sorting
production
Systems
development
Printing
house
co-operation
Master data
maintenance
Sales
Legal
Address
clearance
“Breaking” silos
Virtual team
The strength of different expertise, personalities and
world views and at the same time hampers the
creation of shared understanding
Production data Information
Analytics Analytics Knowledge (what, how, why) Support decision making
As a routine
9. INTERNAL
We have done improvements in several parts of our
process based on analytics.
• The recipient matching 70% => 90%
• Shorten the response time of low-quality
name-address-data (early warning system).
• Adding missing data to the reference DB
• Ongoing improvements of the matching algorithm.
• Better API for printing houses.
• Matching results used to optimize material flows.
• Improving co-operation with mailers and printing
houses.
The most important change has been within virtual
team members.
• We do analysis
• because we want to understand.
• because we want to be better in our work.
• because increased knowledge decrease
uncertainty and ease the decision making.
• to do less mistakes.
13.9.2023
9
Some practical results
Marcus Gustafsson
10. INTERNAL
In traditional information system development reporting and analytics are quite often seen as a
non-functional requirements ~ not so important.
Quite often data analytics are not a core part of the information system development.
Quite often the information system developers are not part of the data analytics.
And still we are talking about using information systems to support the data driven management
and decision making.
This division of development can’t continue if we are aiming for a data driven management.
13.9.2023
10
Concept: IS and analytics development in
co-evolution
Marcus Gustafsson
11. INTERNAL
13.9.2023
11
Developing IS and data analysis in co-evolution
as a routine
Analysis
Information
system
Event data
New
knowledge =>
improvements
For core functionality
and analytics
Doing better analytics
As a routine
Marcus Gustafsson