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When engaging on projects we need to lead our clients to get the outcomes we need for analysis. If we act passively and don’t take charge then they’ll take things all over the place and create chaos. In this article we’ll explore how a problem statement acts as a powerful tool to keep control of our engagement and analysis right through the project lifecycle.

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Taking a product from an abstract idea to an item that’s widely available in the marketplace demands a hands-on approach to prevent things from falling through the cracks. A technique that goes back nearly a century, product lifecycle management (PLM) has for decades been used to improve the efficiency of product development and design.

In recent years, however, a growing number of organizations are realizing the capability of cloud-based PLM software to drive fulfillment benefits. There is a recognition that you can strengthen your supply chain management by deploying PLM from product conception to multi-faceted fulfillment. As your product approaches maturity, it necessitates changes to workflow, supply chain, and fulfillment processes as a means of attaining sales objectives and driving overall business strategy.

But before we get into that and how PLM affects fulfillment, first a definition of PLM.

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Does it make sense to merge Agile philosophies with data science? The short answer is yes, as long as the organization recognizes and accommodates the ambiguous, non-linear nature of the data science process rather than expecting data scientists to fit into the same mold they’ve adopted for “Agile software development”. The problem, in my experience, is that this rarely happens. Probably because the data science field is still new, many organizations are still trying to shoehorn data science into Agile software engineering practices that compromise the natural data science lifecycle.

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Data has emerged as the sole driver of the digital transformation of the present world. It has turned into the most significant resource, and without it, one couldn't really expect to succeed in today's crowded market. Organizations should proficiently utilize their data since it very well may be a factor that can differentiate you in corporate development.  This requires the compelling combination of artificial intelligence with data analytics for enhancing business processes.  The automated direction along with data-driven decision-making is rapidly turning into the standard in this digital world. Since the assortment of data and its analysis is more reachable than any time in recent memory, organizations of all shapes and sizes are leveraging this innovation, hence, noticing noteworthy outcomes. Yet, luring those significant experiences out of your data can be challenging when you reach "big data" extents.

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I’ve written this article to provide an overview of AWS (Amazon Web Services) for Business Analysts.

The cloud (in particular AWS) is now a part of many projects. If you’ve been in meetings where people have mentioned: ‘EC2’, ‘ELB’, ‘AZs’ and thought ‘WTF’ then this article should help you.

This article will provide:

  • an overview of AWS (what is it, why its popular, how it’s used)
  • typical AWS architecture for a project (e.g. VPN, Regions, AZs)
  • cheat sheet for other key terms (EBS, EFS etc)
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This article discusses record types supporting the concepts product, customer, sale, and location. The names given to these records varies depending on the line(s) of business an organization is in and, in particular, the organization’s sales processes.

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There are many other valuable requirements activities besides these six. However, these practices greatly increase your chances of building a solution that achieves the desired business outcomes efficiently and effectively. Applying them doesn’t guarantee success for any BA, product owner, or product manager. But neglecting them likely ensures failure.

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A picture is worth a thousand words. Charts offer visualization and help to understand and comprehend things that would be more painful and time consuming to understand by reading free text. Diagrams help us design systems and processes, organize our screens, while facilitating a common understanding of the big picture. They help us make visible the invisible.

Αs a BA you can exploit a big variety of diagrams to help you communicate better and more accurate information concerning the requirements and the solution. Diagrams leverages the effective use of visuals and modeling techniques in helping organizations and individuals work from the 30,000 foot view down to the level of detail that is needed by those who are actually going to perform the process activities. Moreover a diagram can serve as a single point of truth navigating what should be done and saving time from questions deriving from ambiguous point may found in a text.

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As a data analyst, you feel most comfortable when you’re alone with all the numbers and data. You’re able to analyze them with confidence and reach the results you were asked to find. But, this is not the end of the road for you. You still need to write a data analysis report explaining your findings to the laymen - your clients or coworkers.  That means you need to think about your target audience, that is the people who’ll be reading your report.  They don’t have nearly as much knowledge about data analysis as you do. So, your report needs to be straightforward and informative. The article below will help you learn how to do it. Let’s take a look at some practical tips you can apply to your data analysis report writing and the benefits of doing so.

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This series is about understanding data fundamentals applicable to information systems. In this article and the next, record types specific to an organization’s line(s) of business are discussed. These records support maintaining data for an organization’s Products, Customers, Sales, and sale-related Locations. They will be viewed within the context of five generic line of business functions that represent the business processes involving any product as it goes through its lifecycle.

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Put an end to all your frustration and lost hope; well, the reason and the culprit could be your resume and not your skills or education.
Your resume is your front face or the outfit of your professional profile. Hence it fetches or attracts eyeballs based on its appearance and how it is presented. Here are the 5 top tips to polish your resume to bag the best business analyst jobs...

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A software feature consists of one or more logically related system capabilities that provide value to a user and are described by a set of functional requirements. Many business analysts use features as a way to describe the scope of a project. However, a simple list doesn’t readily show the size and complexity of various features. Nor does quickly skimming a feature list easily reveal the full scope of a project. A feature tree is a visual analysis model that organizes a set of features in a format that makes them easy to understand.

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We begin our exploration of information system data fundamentals by looking at types of records applicable to any organization. Records such as     GL ACCOUNT, STAFF MEMBER, and ASSET are well-understood within any organization large enough to warrant information systems supporting Accounting, Human Resources, or Asset Management functions. These functions and record types are well supported today by commercial off-the-shelf (COTS) packages. So well supported, it’s difficult to imagine any organization justifying a decision to develop an in-house solution rather than buy a commercially available one.

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This is the first of a series of articles intended to help business analysts deal with the information aspect of information systems during requirements elicitation. Requirements are commonly categorized as either functional or non-functional. Given only these two choices, data requirement details are typically included as part of functional requirements. Some may be recorded separately as business rules. By focusing on data fundamentals for information systems, this series hopes that business analysts will be better able to recognize data-specific needs and document them accordingly. 

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A quick way of learning the techniques and skills for becoming a business analyst is to get an internationally recognized certification like ECBA.

ECBA provides a firm understanding and a solid foundation for a business analysis career. It is the entry-level certification from IIBA aimed at professionals stepping into the BA domain.

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