AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

Table of Contents Business Intelligence Solutions for Dynamics

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4 Haunting Statistics of Business Intelligence Projects Gone Wrong

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What is Data Warehouse Automation?

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Why Do BI Projects Fail? 7

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Top 6 Benefits of Data Warehouse Automation (DWA)

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Build Your Data Warehouse with Jet Analytics

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

BUSINESS INTELLIGENCE SOLUTIONS FOR DYNAMICS Microsoft Dynamics is one of the most installed mid-market enterprise resource planning (ERP) systems in the world. With over 130,000 customers, it is a robust and flexible open software platform with a simple interface designed for development and longevity. Although it comes with a pile of reporting and business intelligence (BI) options suitable for all industries, users still have a lot of trouble accessing their data and customizing reports. What’s our real financial standing? How much are we spending? Where does our revenue come from? If any of these questions still leave you scratching your head, there are plenty of solutions out there to help you answer them. These solutions can help you create, format and use the reporting available from Dynamics in an easy-to-understand format for your everyday user. But let’s take a step back and talk about the logistics of actually implementing business intelligence.

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

4 HAUNTING STATISTICS OF BUSINESS INTELLIGENCE PROJECTS GONE WRONG Delayed projects, growing costs, and misaligned expectations have been longstanding problems with business management and analytics software implementations. An independent study completed by Panorama Consulting Solutions in 2017 shares the following data collected on software implementations: • Cost Overages – The average software project cost was $1.3M, with 74% of survey respondents over budget. • Project Delays – The average implementation time was 16.9 months, with 59% of respondents recording setbacks and missed deadlines. • Operational Disruption – 56% of businesses experienced issues with day-to-day operations. • Perceived Value – 37% of the company’s surveyed believe that they received 50% or less of the software benefits promised to them.

Your Dynamics solution includes BI tools like the Role Center, built-in report designer, analysis views, Microsoft Server Reporting Services (SSRS) and SharePoint – but they all require an investment of time, money and resources to make it fit your business operations and data goals. These statistics show that there is a lot of room for error when it comes to the processes required to implement software. For business intelligence and analytics software specifically, you need a “centralized nerve center” provided by the organization’s data warehouse to make your data usable (The Data Warehouse Institute, n.d.). There are traditional approaches to this that are heavy on manual code creation and testing - or you can choose a data warehouse automation platform. This whitepaper focuses on a fast and cost-effective delivery solution to simplify data warehouse design, development, and deployment – leading to the successful adoption of business intelligence in your organization.

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

WHAT IS DATA WAREHOUSE AUTOMATION? A well-implemented data warehouse provides the foundation that enables business intelligence to transform data into usable, actionable information for your business.

Building your BI solution is no different. The parts of the data warehouse lifecycle that demand automation are repetitive, labor intensive and time-consuming, like:

Data warehouse automation (DWA) is a technology and approach designed to build data warehouses efficiently. It reduces resources, costs and project risk by automating your entire data warehousing life cycle from planning, analysis, design and development to operations, maintenance and change management.

• Writing SQL code by hand

The DWA concept has a distinct parallel to manufacturing, where about 100 years ago—thank you, Henry Ford— we realized that there were parts of many processes that demanded automation. Time and money were saved immediately. Efficiency went up and product quality improved.

the components that require more intellectual input than raw technological horsepower.

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• Performing QA cycles • Manual data mapping • Extensive documentation

The idea behind DWA is that if you can automate these time-consuming tasks, then your project team can focus on

In fact, supporters of DWA claim that using it will accomplish an initial BI implementation up to five times faster than traditional methods. This results in a higher success rate for BI projects, and most importantly, it allows for faster, better and more cost-effective delivery of BI output to the business.

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

THE DATA WAREHOUSE AUTOMATION AND BUSINESS INTELLIGENCE LIFECYCLE

PROJECT PLANNING

BUSINESS REQUIREMENTS DEFINITION

TECHNICAL ARCHITECTURE DESIGN

PRODUCT SELECTION & INSTALLATION

DIMENSIONAL MODELLING

PHYSICAL DESIGN

BI APPLICATION SPECIFICATION

GROWTH

ETL DESIGN & DEVELOPMENT

BI APPLICATION DEVELOPMENT

DEPLOYMENT

MAINTENANCE

PROJECT MANAGEMENT

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

WHY DO BI PROJECTS FAIL? One of the widely accepted pitfalls of traditional data warehousing methodology has been that building a BI project is a long, tiring, and expensive process. DWA offers a solution to that, by changing the way we think about building a data warehouse. The expected practice of extensive up-front analysis, design, and modeling is left behind. The mindset changes from ‘get it right the first time’ to ‘develop fast and develop frequently.’ The reasons why most BI projects fail are a result of the traditional data warehousing approach. In this section, we are going to cover three of the most common reasons for extended timelines, increased expenditures, and general dissatisfaction that occur in many BI implementation projects.

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

  1. Manual Data Mapping

  2. Technical Code Creation

Data is messy. Any large data set is guaranteed to have gaps, errors, and

Building a data warehouse and set of OLAP cubes is largely an effort in writing

duplications - among other atrocities. These need to be discovered, understood,

masses of SQL code, which is time-consuming, resource heavy and error-

and rectified before the data can get used. This exercise often takes longer than

prone. Code is what moves data from a source system to a target system, like

expected because there is usually a need to combine several data sets in order

a data warehouse. Code is used to define metrics, create data structures like

to get a full view of company operations.

product hierarchies, and conduct calculations both simple and complex. For

For example, combining CRM information (the date a sales opportunity was entered) with the ERP Financial module (the date a first invoice was posted) will give you sales cycle times and enable financial projections. Now there are two messy data sets to deal with, and in the real world we usually end up

example, it can take a skilled SQL programmer several hours to move a single field from a source database to a target destination.

  1. Organizational Alignment

dealing with many more. This is a great example of a time-consuming, repetitive

A shared vision and understanding of your data must be created to deliver a

task, that doesn’t require human creativity and is better accomplished through

BI product that people will actually use. And this is often the hardest and most

automation.

time-consuming of all tasks. It is vitally important to get everybody on the same

A typical multi-database scenario involves trying to get data from various source systems to match. One system records a specific type of revenue transaction, but it may not be the system of record for the company, and as it turns out, has a different chart of accounts structure. For the revenue transactions to flow into the correct revenue accounts, a mapping exercise must take place. If you were using traditional methods, you would need to write and maintain SQL code to

page about what data is important and how it is to be consumed. Everyone must understand and agree which individual pieces of data will come together to tell the story of the organization and how it is operating. For example, it doesn’t really matter if gross profit is defined as Sales minus COGS, or if it is defined as sales minus COGS plus SGA. What matters is that everyone comes to an agreement on the formula.

handle this mapping in addition to manually documenting any and all changes for data audits.

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

TOP 6 BENEFITS OF DATA WAREHOUSE AUTOMATION Data Warehouse Automation can change more than the way you look at your business, it can change how you do business. Here are six reasons why using DWA can help you successfully adopt BI in your organization and avoid costly project delays and failure.

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

  1. Automates SQL Code Creation You can think of any DWA platform as a code-generating machine. Instead of writing a block of SQL code, you can use a mouse click. That simple click generates a substantial amount of code which compiles in the background. The same underlying tools and processes are used as if it was done by hand, but the difference is that it takes about a second to complete the operation instead of an hour or more of coding. The raw speed advantage is obvious, but since the process is programmatic, (i.e. done by a machine the same way every time), human error is eliminated, testing time is greatly reduced, and re-working the code to fix errors is not necessary. Time and money are saved, and results are delivered faster.

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  1. Eliminates Manual Data Entry Going back to the multi-database scenario, where you have to get data from various source systems to match, DWA would do this in a single click. Instead of the traditional way which requires an experienced resource to write and maintain SQL code, the code would generate in the background in seconds. It is the same for other field transformation tasks, scheduling jobs, and generating documentation – all are candidates for automation. Because of the way it generates mountains of SQL code with the click of a mouse, DWA lets one person do the work of five. It allows you to stop paying people to do something as mindnumbing as writing SSRS scripts. Most importantly, it puts information into the hands of business people five times faster than before.

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

  1. Creates a Shared Vision Between Business Users and IT DWA allows you to combine disparate pieces of data quickly, take them through a complete BI development cycle and deliver results to the business to see if it works. This exercise would be unthinkable in the traditional model because it would take weeks, if not months to do. With DWA, this can be completed in hours, and in essence, it allows you to fail fast. Results can be tested by business users immediately and changed quickly if they are incorrect. At its’ core, DWA allows BI teams to forget about the laborious, time consuming, hands-on work and focus on the ideas. More time is available to work with the business users to find out what information will really make a difference. What KPI’s do we need to catch a trend early? What process change will cut days out of our reporting cycle? How can corporate data be used to save the company time and money? DWA will likely cause you to stop thinking about IT and business folks as two different groups. They end up in the same room so often, talking about results, that they start to form a cohesive team with a collaborative view. Instead of stark and abstract requirements gathering sessions with a long wait time afterward, you have workshop style meetings where business users are communicating, and those ideas get turned into reports and dashboards right in front of them. This iterative style of building BI turns the task of maintenance into a continuation of development. Since it is rare that anybody really knows 100% of their requirements, this method supports the uncertain and changing reality of the business world.

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

  1. Mitigates Risk Every IT project has risk associated with it: Risk of delayed project completion; Risk of going over budget; Risk of low user adoption. Using the traditional method of building a BI solution, the time it takes to create code, verify data, and align metrics, can result in all kinds of unanticipated issues. In the DWA world, the technology part happens so quickly; it changes the way BI projects get built. The traditional requirements gathering phase morphs into more of a priority-setting exercise. This happens because virtually any idea that comes from the business users can be put into effect without a monster effort. Business users’ needs are collected, prioritized and then ‘time-boxed.’ This means that priority number one is evaluated and an estimate is given for how long it will take to build – a day, five days or 10 hours. You can think of each delivery cycle as not only short and quickly followed by another one, but also as its own individual event. The success or failure of the project does not depend upon or affect any other delivery cycle. This means that business users can begin using the most important deliverables as soon as they are ready, while eagerly waiting for the next set to land in their laps.

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

  1. Delivers Rapid Time-to-Value The most intriguing part about the promise of DWA is that it is a technology that solves long-standing problems and has a ripple effect into non-technology issues. It allows us to get to what is important from a BI project: the ability to respond quickly to changing business conditions. Business users are getting what they want, when they want it, as opposed to what they asked for six months ago. Rapid time-to-value is consistently realized since new BI and analytic functionality can be delivered in days, or even hours, instead of months. Shorter implementation times, faster delivery and easier maintenance mean lower costs and a quicker return.

  2. Fulfills User Expectations Business users have expectations that what is promised will be delivered. They need data in a usable format in order to make decisions. Accounts Payable must have accurate information daily to keep the cash coming in. Sales and Purchasing have to know what is in inventory to sell and replenish stocks. If these capabilities are not delivered as promised, you are creating risk on multiple fronts. The shift to DWA enables business users to get what they are asking for very quickly, decide if it is right, and then move on to the next thing. It also accommodates change much better because it doesn’t force the development team to ‘lock down the code’ and declare, “No more changes.” Change is so easy to implement, it becomes part of the process.

DWA is not just a better, cheaper, faster way to build a data warehouse. By its very nature, it changes the way we work. Like true innovation should, it builds on itself to transform our habits and our way of thinking. It changes the things we focus on – we focus on business issues, not technology. DWA inspires productivity and produces results.

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

HOW DO YOU CHOOSE THE RIGHT BI SOLUTION? The BI solution you choose should be easy-to-use, quick to implement, flexible, and built for your Microsoft Dynamics. To help you select the right analytics software, we’ve put together a short but comprehensive webinar on how to choose a BI solution for your Microsoft Dynamics-run business. In this webinar, you will learn: • What you need in a BI solution • What to ask a BI solution provider • What to expect from implementation • Report and dashboard distribution options

WATCH WEBINAR NOW

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AVOID 3 COMMON MISTAKES THAT CAUSE BUSINESS INTELLIGENCE PROJECT FAILURE

BUILD YOUR DATA WAREHOUSE WITH JET ANALYTICS At Jet Global, we know that Dynamics customers need fast access to the right data, but you don’t always have the technical expertise to get it. This impacts your ability to make accurate decisions, build reports and dashboards, and consolidate data in general. That’s why we built Jet Analytics, a corporate analytics and reporting platform that brings your data together for fast, accurate reporting and analysis in Excel, Power BI, and on the web. With a cost-effective data warehouse and pre-built cubes (tabular and OLAP), you can have your BI solution up and running quickly – and start gaining insight into your Dynamics data immediately. Here’s how it works:

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SCHEDULE A DEMO OF JET ANALYTICS FOR DYNAMICS Your Dynamics system has a great foundation for reporting and business analytics. Using Jet Analytics as your BI solution, we take your complex database and simplify it – so your users can design powerful and insightful reports in an Excel-based environment on their own. At Jet Global, our solutions are specifically built for Dynamics end users and work immediately out-of-the-box, cutting your costs by 50%. Take the first step towards effective change and tangible BI results and see what Jet Analytics can bring to your business.

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See for yourself why 14,210 customers from 94 countries trust Jet Global to manage their Microsoft Dynamics data.

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