A Strategic View of Enterprise Reporting and Analytics: The Data FunnelInside Analysis
The Briefing Room with Colin White and Jaspersoft
Slides from the Live Webcast on June 12, 2012
As the corporate appetite for analytics and reporting grows, companies must find a way to secure a strategic view of their information architecture. End users with varying degrees of expertise need a wide range of data and reports delivered in a timely fashion. As the audience for analytics expands, that puts pressure on IT infrastructure and staff. And now with the promise of Hadoop and MapReduce, the organization's desire for business insight becomes even more significant.
In this episode of The Briefing Room, veteran Analyst Colin White of BI Research will explain the value of being strategic with enterprise reporting. White will be briefed by Karl Van den Bergh of Jaspersoft, who will tout his company's “data funnel” concept, which is designed to strategically manage an organization's information architecture. By aligning information assets along this funnel, IT can effectively address the spectrum of analytical needs – from simple reporting to complex, ad hoc analysis – without over-taxing personnel and system resources.
Critical success factors to develop and deliver a forward-looking BI strategy...SAP Analytics
sap.com/analytics - This SAPinsider #BI2015 session attendees will learn key elements of an effective BI strategy that benefits both IT and the core business alike.
How to implement a Business Intelligence Strategy - Kevin CrowleyHodge
Hodge's Head of Business Intelligence Kevin Crowley presenting how to implement a Business Intelligence Strategy, presented at the CIM Analytics Masterclass
Presentation I put together while at Business Objects where I spearheaded the development of the Business Intelligence Competency Center practice and service offering.
A Strategic View of Enterprise Reporting and Analytics: The Data FunnelInside Analysis
The Briefing Room with Colin White and Jaspersoft
Slides from the Live Webcast on June 12, 2012
As the corporate appetite for analytics and reporting grows, companies must find a way to secure a strategic view of their information architecture. End users with varying degrees of expertise need a wide range of data and reports delivered in a timely fashion. As the audience for analytics expands, that puts pressure on IT infrastructure and staff. And now with the promise of Hadoop and MapReduce, the organization's desire for business insight becomes even more significant.
In this episode of The Briefing Room, veteran Analyst Colin White of BI Research will explain the value of being strategic with enterprise reporting. White will be briefed by Karl Van den Bergh of Jaspersoft, who will tout his company's “data funnel” concept, which is designed to strategically manage an organization's information architecture. By aligning information assets along this funnel, IT can effectively address the spectrum of analytical needs – from simple reporting to complex, ad hoc analysis – without over-taxing personnel and system resources.
Critical success factors to develop and deliver a forward-looking BI strategy...SAP Analytics
sap.com/analytics - This SAPinsider #BI2015 session attendees will learn key elements of an effective BI strategy that benefits both IT and the core business alike.
How to implement a Business Intelligence Strategy - Kevin CrowleyHodge
Hodge's Head of Business Intelligence Kevin Crowley presenting how to implement a Business Intelligence Strategy, presented at the CIM Analytics Masterclass
Presentation I put together while at Business Objects where I spearheaded the development of the Business Intelligence Competency Center practice and service offering.
Microsoft Business Intelligence Vision and StrategyNic Smith
Microsoft Business Intelligence slide deck, learn the Microsoft vision and strategy for business intelligence. These slides include the offering and value proposition for Microsoft BI.
A presentation from TDWI's 2009 Executive Summit in San Diego. This presentation is by Wayne Eckerson, TDWI's Director of Research. For more information on TDWI, please visit http://www.tdwi.org
Agile BI: How to Deliver More Value in Less TimePerficient, Inc.
Learn how to:
Construct a BI and analytical environment that provides the critical functionality that enables your customers to provide timely answers, supporting modern agile business
Leverage agile delivery concepts to deliver value in days rather than in months
Build a support organization that enables your users to create increased value from your company’s information assets
Modern Business Intelligence - Design and ImplementationsDavid J Rosenthal
During the first two “waves” of business intelligence, IT professionals and business analysts were the keepers of BI. They made BI accessible and consumable for end users.
While this approach still applies to complex business intelligence needs, today there is a new “wave.” This third wave of BI makes BI available to every kind of user.
As customer strive to take advantage of the digital transformation that is occurring in virtually every industry, they need to re-evaluate how they engage with their customers/prospects, how they transform their products and operations, and how they empower and understand their employees.
In today’s world, doing each of these things is more and more reliant upon data…traditionally, everything you knew about your customers and prospects was available in your business application systems and in the heads of employees. You learned almost everything about your products BEFORE they left your warehouse. Employees used technology more to enter data than to learn from it.
In the data-driven world we live in today, leveraging intelligent insights from data across customers, products, and employees is critical to be able to stay competitive and keep up with or lead digital transformation in any industry. And this isn’t just a customer’s typical business application data – it’s also about augmenting the customer’s data with additional data (e.g. search, employee behavioral data, sentiment data, benchmark data, etc..) – and applying the right intelligence to drive meaningful insights.
Oracle BI Applications: Delivering Value Through Rapid ImplementationsKPI Partners
Providing actionable business intelligence across the enterprise to enable informed decision-making and streamlined business processes is an obtainable goal. Team members from Oracle and KPI Partners presented this virtual event that helps provide the basic foundation and understanding you need in order to know where to start, how to select trusted advisors, how to form your team, how to set user expectations, and what pitfalls to avoid.
Guests Simon Miller and William Hutchinson have recently authored a new book within the Oracle Press series titled 'Oracle Business Intelligence Applications: Deliver Value Through Rapid Implementations'. Their book serves as a guide to anyone who has been touched by an Oracle BI Applications purchase and implementation, including CXOs, business managers, functional end users, implementers, IT support, and data warehouse professionals.
With over 25 years of experience, Simon and Will can help provide perspective into several areas:
-Why you would consider purchasing a pre-built analytic application?
-The challenges and risks of building a data warehouse from scratch
-Are Oracle BI Applications applicable for your needs?
-What should you be aware of when implementing?
-How can you extend and make a pre-built BI application your own?
-How can Exalytics help with a deployments?
-Understanding of the different technical components of Oracle BI Applications
-What does Oracle's out-of-the-box BI application include in terms of content?
Those who joined us had the opportunity to see Oracle BI Applications through the eyes of two tenured individuals who have built their careers around explaining what the BI Applications are and how they can help an organization.
Guests:
Simon Miller is a Master Principal Sales Consultant at Oracle, specializing in Oracle’s prebuilt BI Applications. Over the past 15 years he has worked exclusively in the BI Technology, Architecture, and Analytics space across North America and parts of Europe. Simon was originally trained on what is now Oracle’s prebuilt BI Applications in April 2002. He is responsible for working with one of Oracle’s largest customers, supporting both evaluations and implementations of Oracle BI Applications.
William Hutchinson is a Master Principal Sales Consultant at Oracle, specializing in Oracle’s BI tools and applications. He has worked in business intelligence and data warehousing for more than 25 years. Will started building data warehouses in 1986, working at Informatica and Siebel, before coming to Oracle as part of the Siebel acquisition.
Sid Goel, Partner and BI Architect, KPI Partners
Sid is responsible for the overall technology direction, strategy, and methodology development of KPI Partners operations. He has over ten years of experience strategizing and developing innovative Business Intelligence and CRM solutions.
This presentation contains strategies that BI groups within IT can use to maximize their productivity and value to the business. It contains an overview of why and how ‘agile BI’ is used at direct-marketing leader Valpak, and several other strategies that can be employed to help deliver timely, effective BI solutions.
Five Attributes to a Successful Big Data StrategyPerficient, Inc.
The veracity, variety and sheer volume of data is increasing exponentially. With Hadoop and NoSQL solutions becoming commonplace, there are many technical options for managing and extracting value from this data. Many companies create labs to experiment with Big Data solutions, only later become IT playgrounds or unstructured dumping grounds.
To help avoid these pitfalls,companies with successful Big Data projects approach challenges by formulating a strategy that assures real business value is derived from their Big Data investments. In a Perficient poll, 73% of companies stated they are in the early-evaluation stage to find solutions to their Big Data problems and are only beginning to create their strategy.
Join us for a webinar featuring thought-provoking best practices used by successful companies to quickly realize business value from their Big Data investments. You'll learn:
The top five steps to increased business value
What the top companies are doing in Big Data that you need to know
Next steps to lay the ground work for a successful Big Data strategy
Gartner: The BI, Analytics and Performance Management FrameworkGartner
Further information on BI is available at www.gartner.com. Gartner will also host its Business Intelligence Summit 2011, 31 Jan- 1 Feb, London. More information at www.europe.gartner/bi.
Microsoft Business Intelligence Vision and StrategyNic Smith
Microsoft Business Intelligence slide deck, learn the Microsoft vision and strategy for business intelligence. These slides include the offering and value proposition for Microsoft BI.
A presentation from TDWI's 2009 Executive Summit in San Diego. This presentation is by Wayne Eckerson, TDWI's Director of Research. For more information on TDWI, please visit http://www.tdwi.org
Agile BI: How to Deliver More Value in Less TimePerficient, Inc.
Learn how to:
Construct a BI and analytical environment that provides the critical functionality that enables your customers to provide timely answers, supporting modern agile business
Leverage agile delivery concepts to deliver value in days rather than in months
Build a support organization that enables your users to create increased value from your company’s information assets
Modern Business Intelligence - Design and ImplementationsDavid J Rosenthal
During the first two “waves” of business intelligence, IT professionals and business analysts were the keepers of BI. They made BI accessible and consumable for end users.
While this approach still applies to complex business intelligence needs, today there is a new “wave.” This third wave of BI makes BI available to every kind of user.
As customer strive to take advantage of the digital transformation that is occurring in virtually every industry, they need to re-evaluate how they engage with their customers/prospects, how they transform their products and operations, and how they empower and understand their employees.
In today’s world, doing each of these things is more and more reliant upon data…traditionally, everything you knew about your customers and prospects was available in your business application systems and in the heads of employees. You learned almost everything about your products BEFORE they left your warehouse. Employees used technology more to enter data than to learn from it.
In the data-driven world we live in today, leveraging intelligent insights from data across customers, products, and employees is critical to be able to stay competitive and keep up with or lead digital transformation in any industry. And this isn’t just a customer’s typical business application data – it’s also about augmenting the customer’s data with additional data (e.g. search, employee behavioral data, sentiment data, benchmark data, etc..) – and applying the right intelligence to drive meaningful insights.
Oracle BI Applications: Delivering Value Through Rapid ImplementationsKPI Partners
Providing actionable business intelligence across the enterprise to enable informed decision-making and streamlined business processes is an obtainable goal. Team members from Oracle and KPI Partners presented this virtual event that helps provide the basic foundation and understanding you need in order to know where to start, how to select trusted advisors, how to form your team, how to set user expectations, and what pitfalls to avoid.
Guests Simon Miller and William Hutchinson have recently authored a new book within the Oracle Press series titled 'Oracle Business Intelligence Applications: Deliver Value Through Rapid Implementations'. Their book serves as a guide to anyone who has been touched by an Oracle BI Applications purchase and implementation, including CXOs, business managers, functional end users, implementers, IT support, and data warehouse professionals.
With over 25 years of experience, Simon and Will can help provide perspective into several areas:
-Why you would consider purchasing a pre-built analytic application?
-The challenges and risks of building a data warehouse from scratch
-Are Oracle BI Applications applicable for your needs?
-What should you be aware of when implementing?
-How can you extend and make a pre-built BI application your own?
-How can Exalytics help with a deployments?
-Understanding of the different technical components of Oracle BI Applications
-What does Oracle's out-of-the-box BI application include in terms of content?
Those who joined us had the opportunity to see Oracle BI Applications through the eyes of two tenured individuals who have built their careers around explaining what the BI Applications are and how they can help an organization.
Guests:
Simon Miller is a Master Principal Sales Consultant at Oracle, specializing in Oracle’s prebuilt BI Applications. Over the past 15 years he has worked exclusively in the BI Technology, Architecture, and Analytics space across North America and parts of Europe. Simon was originally trained on what is now Oracle’s prebuilt BI Applications in April 2002. He is responsible for working with one of Oracle’s largest customers, supporting both evaluations and implementations of Oracle BI Applications.
William Hutchinson is a Master Principal Sales Consultant at Oracle, specializing in Oracle’s BI tools and applications. He has worked in business intelligence and data warehousing for more than 25 years. Will started building data warehouses in 1986, working at Informatica and Siebel, before coming to Oracle as part of the Siebel acquisition.
Sid Goel, Partner and BI Architect, KPI Partners
Sid is responsible for the overall technology direction, strategy, and methodology development of KPI Partners operations. He has over ten years of experience strategizing and developing innovative Business Intelligence and CRM solutions.
This presentation contains strategies that BI groups within IT can use to maximize their productivity and value to the business. It contains an overview of why and how ‘agile BI’ is used at direct-marketing leader Valpak, and several other strategies that can be employed to help deliver timely, effective BI solutions.
Five Attributes to a Successful Big Data StrategyPerficient, Inc.
The veracity, variety and sheer volume of data is increasing exponentially. With Hadoop and NoSQL solutions becoming commonplace, there are many technical options for managing and extracting value from this data. Many companies create labs to experiment with Big Data solutions, only later become IT playgrounds or unstructured dumping grounds.
To help avoid these pitfalls,companies with successful Big Data projects approach challenges by formulating a strategy that assures real business value is derived from their Big Data investments. In a Perficient poll, 73% of companies stated they are in the early-evaluation stage to find solutions to their Big Data problems and are only beginning to create their strategy.
Join us for a webinar featuring thought-provoking best practices used by successful companies to quickly realize business value from their Big Data investments. You'll learn:
The top five steps to increased business value
What the top companies are doing in Big Data that you need to know
Next steps to lay the ground work for a successful Big Data strategy
Gartner: The BI, Analytics and Performance Management FrameworkGartner
Further information on BI is available at www.gartner.com. Gartner will also host its Business Intelligence Summit 2011, 31 Jan- 1 Feb, London. More information at www.europe.gartner/bi.
Excelogic Consulting and Training Experience
- Logistics/Supply Chain Management
- Quality, Health and Safety Environment
- Business Management
Visit Our Website http://excelogic.info/
Email : admin@excelogic.info
I am Murali.Below is a short summary on my professional experience,
Total years of experience - 13 (Releavant BO experience - 10 Years)
Technologies/Tools worked on : SAP BO 4.x - XI R2,BO Admin, Xcelsius Dashboard designing, Crystal Reports, SAP Design Studio, SAP BW 7,Unix,Oracle 10G PL/SQL, SQL Server and Microsoft Technologies(VB,ASP and VB.Net).
I am interested to take up new roles on different aspects in BO domain.
Business Intelligence (BI) solutions can help manufacturing business users to analyse cost factors and make appropriate decisions for acquisition of raw material and sold goods.
Building a 360 Degree View of Your Customers on BICSPerficient, Inc.
Why there is a need for Customer 360 and what the proposed cloud based solution is. We cover the stages of strategic marketing and how Oracle BI can help.
Join the professionals at BAASS as we answer your key quesons about Business Intelligence and how it can fit
within your business model. Dive deeper into how varying
soluons offered by our vendors can cater specifically to your business needs. Uncover technology that transforms raw data into meaningful and useful informaon for your key business funcons. You’ll hear from a wide range of
presenters and be able to uncover details regarding each of the following Business Intelligence Tools:
1. BAASS Business Intelligence
2. Sage Business Intelligence
3. Info Explorer
4. BI Metrix
5. Data Warehousing BI
See how Business Intelligence can be practically applied in the Mid-Market. This presentation is about how a tool once out of their reach of Mid-Market companies is now in their grasp and how they can apply it in practical business applications
Asyma E3 2014 The 5 Biggest Business Challenges and some tools to help you ...asyma
Orchid Systems’ Information Manager is a useful tool for combining and managing all business data in Sage 300 ERP and eliminates the need for costly data warehouses. The suite of tools includes an OLAP (Online Analytical Processing) solution called Info Explorer. Info Explorer makes it easy for users to combine and manage all business data in Sage 300 ERP (Accpac) as well as other application data for multidimensional “cube” analysis such as Product, Sales, Profitability or Commission Reports and Financial/Income Statement data without the need for multiple Crystal or FR Reports.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfGetInData
Recently we have observed the rise of open-source Large Language Models (LLMs) that are community-driven or developed by the AI market leaders, such as Meta (Llama3), Databricks (DBRX) and Snowflake (Arctic). On the other hand, there is a growth in interest in specialized, carefully fine-tuned yet relatively small models that can efficiently assist programmers in day-to-day tasks. Finally, Retrieval-Augmented Generation (RAG) architectures have gained a lot of traction as the preferred approach for LLMs context and prompt augmentation for building conversational SQL data copilots, code copilots and chatbots.
In this presentation, we will show how we built upon these three concepts a robust Data Copilot that can help to democratize access to company data assets and boost performance of everyone working with data platforms.
Why do we need yet another (open-source ) Copilot?
How can we build one?
Architecture and evaluation
2. Agenda
1. To Create is to Own
2. Synthesize and Collaborate
3. Build a Plan, Sell it, Deliver it
3. History
1. Strategy project in 2007
2. Architecture issues
3. Questions around toolset strategy
4. Departmental coverage issues
5. Reporting model issues
4. Limited Progress to mid-2011
1. Strategy had not been refreshed…limited focus
2. No agreed program of work…resourcing issues
3. Technical landscape unclear
5. To Create is to Own
1. We didn’t create it
2. It wasn’t in our own words
3. We didn’t own it
6. • Implement Business Objects BI4
• Migrate to SAP Hana (Dev/Test/Prod)
• Implement BPC
• Build Simplified Architecture
• Migrate Cube Content
Technical
Migration
Re-Architect
For Hana
• Promote New Tools
• Retire Cubes / Excel
• Target Worst Performing Reports……
User Migration
Technical Progress in 2012
7. 2013…Back to Basics
1. What exactly is an IT or BI strategy?
2. Why bother…it’s a lot of work
3. What does it look like…it must be simple
8. Synthesize and Collaborate
“Combine (a number of things) into a coherent whole”
“The action of working with someone to produce something”
(The Oxford Dictionary)
1. Key stakeholder workshops - collaboration
2. Business Function Engagement
BFA4’s
3. IT Collaboration and Synthesis
9. 2. FlitePlan Approach
IT Strategic Planning Methodology
Set-up
& Prep
Themes &
Messages
Business
Function
Strategies
IT Function
Domain
Strategies
Enterprise
context &
strategy
IT
context & trends
Road
MapsIT Value Proposition & Vision
EFM
ITVP
BFa4
FM&DPs
links
1 Page
collab
11. BI Function RAG Status
1 Initial 2 Basic 3 Intermediate 4 Advanced 5 Optimal
Toolsets
-Data Analysis
-ETL
-Rpt writing
Support adhoc data
analysis
SUPPORT ANALYSIS CAPABILITY
Provide analysis tool
training & support
Administer access to
Analysis tools
Select & maintain
Tools Create & maintain
Data architecture
Administer and run
ETL processes
CREATE & MAINTAIN DATA REPOSITORIES
Data
Repositories
Design & develop reports
CREATE & SUPPORT DISTRIBUTABLE ANALYTICS
Develop & communicate
training documentationGather & analyse
requirements
Support & Maintain
Reports
Adv Analytics
Dashboards
GOVERN BI PORTFOLIO & PIPELINE
BI&R
Architecture
Build & maintain BI
KDM relationships
Oversee and Prioritise
BI&R pipeline & portfolio
BI&R
Roadmap
Manage vendors &
suppliers
Tools
BI CC
Standard
Reports
Design & develop
Analytics / Dashboards
Build & Maintain Semantic
Layer
Semantic
Layers
Develop & communicate
Data Dictionary
12. CURRENT STATE
• Cutting edge database platform for BW
• SAP Native ETL (extractors from ECC to
BW)
• Multiple strategies and platforms
• Multiple semantic approaches
• Multiple ETL technologies
• Redundancy across multiple technologies
• User skill level for tools
• Definitions, KPIs and lineage unclear
• Highly complex data processing
2
Example: Repositories
FUTURE STATE
• Condensed ETL processes
• Single re-usable repository
• Hana centric repositories
• End to End integrated SAP
• Data Definitions and Dictionary
DEFINITION – Create and Maintain Data Repositories – ETL Processes, Data Repositories, Data Quality, Semantic Layers,
Definitions and Documentation
INITIATIVES
1. Replicate existing Microsoft Analysis cube data requirements in BW/Hana
2. Produce definitions and Data Dictionary
5
13. SEMANTIC (DE-GEEK) LAYERS
xx
Business Intelligence Overview
At Frucor, BI is an IT function that supports corporate
data, reporting, analysis and advanced analytics for
decision-making through information analysis.
Business Intelligence (BI) is an umbrella term that includes the applications,
infrastructure and tools, and best practices that enable access to and analysis of
information to improve and optimize decisions and performance - Gartner
SERVERS
xx
USERS
xx
REPORTS
xx
QUERIES
xx
DATABASES
xx
xx
APPLICATIONS
Maintain Repositories
& Semantic layers
Data
Repositories &
Semantic Layers
Provide tools and Support
Analysis Capability
Analytic
Tools
Create & support
Standard Reports & Analytics
Standard Reports
& Analytics
Govern BI portfolio
& work pipeline
BI Toolsets
For
Information
Consumers
Behind the
scenes for
everyone
For
Information
Analysts
14. BI Current State: Business View
Create & support
standard reports & analytics
Provide tools & support
Analysis capability
Manage Data Repositories
and Semantic layers
Data
Repositories
& Semantic
Layers
Advanced
Analysis
Tools
Standard
Reports
& Analytics
Govern BI portfolio
and work pipeline
BI Toolsets
Good enough OK but we want to improve High priority focus
• There is a lack of access to quality
reports and Information
• Self-service hasn’t worked for core
reporting, why can’t IT provide this?
• There is a significant lack of
Reporting resource
• There is confusion regarding tool
selection
• There is a lack of skill in the use of
our tools
• Frucor’s BI system has insufficient
coverage of our Business
For
Information
Consumers
Behind the
scenes for
everyone
For
Information
Analysts
Source … - Australia and New Zealand BI Strategy Workshops (Mar / Apr ’13)
- 1 on 1 interviews with Directors through IT Strategy Initiative (Apr / May ‘13)
15. BI Vision and Strategy
VISION:
Timely insights for better
decisions
Rationalise our tools
IT capacity to engage, educate and evangelise
Leverage BI for competitive
advantage
IT delivers standard reporting capability (own the last mile)
Co-invest in growing Frucor BI
capability
Better insights through visual, mobile and predictive analytics
Co-invest to grow coverage and capability
Run Grow & Transform
16. Building the Plan
• Director Support Essential
• Co-investment
– #1 priority was to get commitment for their key people’s time
– Invest in “information analyst” capability with a training budget
– IAs commit to training, using new tools and phasing out old tools
What we asked for:
17. Building the Plan
• Co-investment through BI Sprints
– One sprint per country per quarter
– Department has the full focus of the BI team for the quarter
– A BI budget for developing data extracts
– Senior BI analyst embedded in the department for six weeks
What we offered:
19. Lessons Learned
1. External support helps with process…own it internally
2. Start early…it can take a while
3. Synthesis and collaboration…that’s the key
Strategy:
20. Lessons Learned
1. Director ownership is essential
2. Run each sprint as a separate project - time boxed
3. Create a dust storm…communicate success
Planning & Delivery:
21. Wrap Up
1. To Create is to Own
2. Synthesize and Collaborate
3. Build a Plan, Sell it, Deliver it
Editor's Notes
Classic model: seek input through focus groups or online surveys.
Staff are invited to volunteer ideas, all the ideas generated are given to someone else to work on.
Limited stakeholder buy in
Take control of the way things work in your sphere of influence
We didn’t go through the birthing pains…we didn’t give birth to it
User Migration:
The biggest issue was and still is ownership, the business sees it as IT’s job, current position is this is a business function
Forcing Migration of all cube content created work, work we didn’t own and the business didn’t see value in and did not want to do
The worst performing reports were no longer performing too bad – could have continued and tick the boxes, but that would not have added value, was not good for the business or IT
What is it:
”A clear statement of intent. It states what you consider to be the best way to achieve your objectives using the capabilities and opportunities you have available”
A strategy is not a plan but it informs, or gives direction to, a plan
Why bother:
It helps your team to work smarter, not harder.
It gives you the reasons to say “no” to requests that don’t contribute to the organisation’s objectives.
It helps define BI’s role and contribution to the organisation.
It helps to improve efficiency and effectiveness by reducing wasted effort.
It improves staff morale and engagement by providing focus and direction.
What does it look like:
“What has not been made simple cannot be made clear and what is not clear will not be done.”
Be pragmatic: using the capabilities and opportunities available
1 – Future State
Workshop Frucor’s ideal BI environment, if we were excelling in the use of BI, what would that look like?
2 – Current State
Reality Check! What does our environment look like now? What works, what doesn’t, what are the frustrations?
3 – Bridging the GAP
1 – 2 Knowing where we want to be and where we are, identify the gaps, what needs to be done to address them and set priorities.
How did we go about developing the strategy?
Worked with a partner to keep us on track…followed a methodology.
Linked to business strategy
Adv Analytics Dashbds
Lots of detail behind the scenes…that’s why synthesis and collaboration are so important to distil it down
… Our vision for … Business Intelligence and Reporting … is to provide “Timely insights for better decisions” …
… This one of our priority areas for strategy … our strategies are ..
… Co-invest to grow Frucor BI capability
… Continue to simplify our BI technology …
… looking at the Roadmap initiatives … click
For each sprint a business case is built and presented to the directors in both NZ and AU
Director buy-in:
- took a portfolio approach.
- reminded them of feedback through BI workshops and BFA4’s
- discussed priorities
Project:
- remember it’s their project
- expect and demand full engagement
- good governance – spinnaker not anchor - not bureaucratic
- be straight up – very important