334 Analytics courses

Better Business Cases™ Practitioner Better Business Cases™ is based on the Five Case Model - which is the UK government's best practice approach to structuring spending proposals and making effective business decisions. Using this best-practice approach will allow organizations to reduce unnecessary spending and improve the decision-making process which gives you a greater chance of securing necessary funding and support for initiatives. The goal of the practitioner course is to develop a candidate's ability to deliver a comprehensive business case, through encouraging expanded knowledge to guide the practical application of theoretical foundations. Upon the completion of this Practitioner course, a candidate will be able to start applying the model to a real business case development project. What You Will Learn At the end of this program, you will be able to: Develop the lifecycle of a business case and to establish the relationships between the five cases Apply the steps in the business case development framework, in order to support the production of a business case, using the Five Case Model, for a given scenario Overview of Better Business Cases Alignment with the strategic planning process Importance of the Business Case using the Five Case Model Overview of the Five Case Model Purpose of the key stages in the development of a spending proposal Purpose of a Business Justification Case Business Case Development Process Purpose of project / programme assurance and assurance reviews Responsibility for producing the Business Case Determining the Strategic Context and Undertaking the Strategic Assessment Scoping the Scheme and Preparing the Strategic Outline Case Planning the Scheme and Preparing the Outline Business Case Procuring the Solution and Preparing the Full Business Case Implementation and monitoring Evaluation and feedback Making the Case for Change Agree on the strategic context Determine spending objectives, existing arrangements, and business needs Determine potential business scope and key service requirements Determine benefits, risks, constraint, and dependencies Exploring the Preferred Way Forward Agree on critical success factors Determine long list options and SWOT analysis Recommend a preferred way forward Determining Potential Value for Money Revisit the short list Prepare the economic appraisal for short-listed options Undertake benefits appraisal Undertake risk appraisal Select preferred option and undertake sensitivity analysis Preparing for the Potential Deal Determine the procurement strategy Determine service streams and required outputs Outline potential risk apportionment Outline potential payment mechanisms Ascertain contractual issues and accountancy treatment Ascertaining Affordability and Funding Requirement Prepare the financial model Prepare the financial appraisals Planning for Successful Delivery Plan programme / project management Plan change and contract management Plan benefits realization Plan risk management Plan programme / project assurance and post project evaluation Procuring the Value for Money Solution Revisit the case for change Revisit the OBC options Detail procurement process and evaluation of best and final offers (BAFOs) Contracting for the Deal Set out the negotiated deal and contractual arrangements Set out the financial implications of the deal Ensuring Successful Delivery Finalize project management arrangements and plans Finalize change management arrangements and plans Finalize benefits realization arrangements and plans Finalize risk management arrangements and plans Finalize contract management arrangements and plans Finalize post-project evaluation arrangements and plans

Business Process Modeling: In-House Training This course is part of IIL's Business Analysis Certificate Program (BACP), a program designed to help prepare individuals pass the IIBA® Certification exam to become a Certified Business Analysis Professional (CBAP®). Learn more at www.iil.com/bacp A process model is a description of a process in terms of its steps or actions, the data flowing between them and participants in the process, machines, systems, and organizations involved. Modeling is a critical business analysis skill. It applies graphical and text communication techniques to describe the actions, objects, and relationships acted upon in the process and the steps that act upon them. This course teaches the technique of process modeling and ties together the core methods of process, behavior, and data modeling to enable business analysts to fully describe business processes in levels of detail from multiple perspectives. What you will Learn Upon completion, participants will be able to: Identify business processes and their components Work with UML diagrams Use process modeling in business diagramming Diagram and model business processes Foundation Concepts The role of the business analyst The IIBA® BABOK® Knowledge Areas Business Process Modeling (BPM) and the business analyst A practical approach to business process modeling The Context for Modeling Business Processes Overview of context for business process modeling Analyzing stakeholder information Modeling best practices Critical inputs for BPM: Business Rules Critical inputs for BPM: Context Diagrams Data Models Overview of data modeling Entity relationship diagrams Object-oriented approach Class diagrams Other data models Process Models - Part I (Non-UML) Overview of process modeling Data flow diagrams Workflow diagrams Flowcharts Process Models - Part II (UML) Overview of UML Process Models UML Activity Diagrams UML Sequence Diagrams Usage Models - Part I (Non-UML) Overview of usage modeling Prototyping options Static prototyping and storyboards Dynamic prototyping User Interface Design and user stories Usage Models - Part II (UML Use Cases) Overview of Use Cases Use Case diagrams Use Case descriptions Use Cases and the product life cycle Integrating the Models Overview of integrating the models General analysis best practices Specific analysis techniques summary Best practices for transition to design Summary and Next Steps What did we learn and how can we implement this in our work environments?

This course will allow you to explore the potential of self-service business intelligence using Power BI Desktop to analyse and connect to different sources of data, creating Relationships between those different datasets, Query the data using Shaping and data Modelling, to create Visualizations, and publish Reports to different platforms . Course Objectives At the end of this course you will be able to: Connect to data from different sources. Use the Query Editor Perform Power BI desktop data Shaping and Transformation. Create Power BI desktop Modelling. Create Power BI desktop Visualizations and Reports. ' 1 year email support service Take a closer look at the consistent excellent feedback from our growing corporate clients visiting our site ms-officetraining co uk With more than 20 years experience, we deliver courses on all levels of the Desktop version of Microsoft Office and Office 365; ranging from Beginner, Intermediate, Advanced to the VBA level and Business Intelligence. Our trainers are Microsoft certified professionals with a proven track record with several years experience in delivering public, one to one, tailored and bespoke courses. Our competitive rates start from £550.00 per day of training Tailored training courses: You can choose to run the course exactly as they are outlined by us or we can customise it so that it meets your specific needs. A tailored or bespoke course will follow the standard outline but may be adapted to your specific organisational needs. Please visit our site (ms-officetraining co uk) to get a feel of the excellent feedback our courses have had and look at other courses you might be interested in. Introduction to Power BI Power BI Jargon explained A quick look at Power BI Desktop A quick look at the Power BI service Helpful resources Power BI and Excel Introduction to using Excel data in Power BI Upload Excel data to Power BI Import Power View and Power Pivot to Power BI Getting started with Power BI Desktop Overview of Power BI Desktop Accessing Help and Helpful resources Connect to data sources in Power BI Desktop Shaping and Transforming Data with Query Editor Introduction to the Query Editor Data Sources Power BI Desktop can Connect to Introduction to Steps and M code Combining Data Using Merge and Append Queries Data Type Properties Working with Delimiters Clean and transform your data with the Query Editor Text Specific Transformation Tools Number Specific Transformation Tools Date Specific Transformation Tools Split and Merge columns Creating an Index Column Adding Conditional Columns Columns From Examples Grouping and Aggregating data Pivoting and Unpivoting Using filters Modeling the data Introduction to modeling your data How to manage your data relationships Create calculated columns Optimizing data models Create calculated measures Show Values As and Quick Measures Create calculated tables Explore your time-based data Introduction to DAX DAX calculation types DAX functions Visualizations Introduction to visuals in Power BI Create and customize simple visualizations Modify colors in charts and visuals Shapes, text boxes, and images Page layout and formatting Group interactions among visualizations Visual hierarchies and drill-down Using custom visualizations Create a KPI Visualization Geo-Data and Maps Reports, Publishing and Sharing Introduction to the Power BI service Quick insights in Power BI Create and configure a dashboard Ask questions of your data with natural language Create custom Q&A suggestions Share dashboards with your organization Introduction to content packs, security, and groups Publish Power BI Desktop reports Print and export dashboards and reports Create groups in Power BI Use content packs Update content packs Publish to web Who is this course for? Who is this course for? This course facilitates you with knowledge on the potential for Power BI Desktop to analyse and connect to different sources of data, creating Relationships between those different datasets, Query the data using Shaping and data Modelling, and to create Visualizations, and publish Reports to different platforms. Requirements Requirements Before attending this course, delegates should have: - A general knowledge of database concepts (fields, records and relationships) - Familiarity with Excel. Career path Career path Business Intelligence Data Analysis ETL & Data Warehousing

FourSquare Training specialise in private, corporate Power BI courses delivered at your premises and tailored to your needs.

This course will allow you to explore the potential of self-service business intelligence using Power BI Desktop to analyse and connect to different sources of data, creating Relationships between those different datasets, Query the data using Shaping and data Modelling, to create Visualizations, and publish Reports to different platforms . Course Objectives At the end of this course you will be able to: Connect to data from different sources. Use the Query Editor Perform Power BI desktop data Shaping and Transformation. Create Power BI desktop Modelling. Create Power BI desktop Visualizations and Reports. ' 1 year email support service Take a closer look at the consistent excellent feedback from our growing corporate clients visiting our site ms-officetraining co uk With more than 20 years experience, we deliver courses on all levels of the Desktop version of Microsoft Office and Office 365; ranging from Beginner, Intermediate, Advanced to the VBA level and Business Intelligence. Our trainers are Microsoft certified professionals with a proven track record with several years experience in delivering public, one to one, tailored and bespoke course Tailored training courses: in in company training, you can choose to run the course exactly as they are outlined by us or we can customise it so that it meets your specific needs. A tailored or bespoke course will follow the standard outline but may be adapted to your specific organisational needs. Please visit our site (ms-officetraining co uk) to get a feel of the excellent feedback our courses have had and look at other courses you might be interested in. Introduction to Power BI Power BI Jargon explained A quick look at Power BI Desktop A quick look at the Power BI service Helpful resources Power BI and Excel Introduction to using Excel data in Power BI Upload Excel data to Power BI Import Power View and Power Pivot to Power BI Getting started with Power BI Desktop Overview of Power BI Desktop Accessing Help and Helpful resources Connect to data sources in Power BI Desktop Shaping and Transforming Data with Query Editor Introduction to the Query Editor Data Sources Power BI Desktop can Connect to Introduction to Steps and M code Combining Data Using Merge and Append Queries Data Type Properties Working with Delimiters Clean and transform your data with the Query Editor Text Specific Transformation Tools Number Specific Transformation Tools Date Specific Transformation Tools Split and Merge columns Creating an Index Column Adding Conditional Columns Columns From Examples Grouping and Aggregating data Pivoting and Unpivoting Using filters Modeling the data Introduction to modeling your data How to manage your data relationships Create calculated columns Optimizing data models Create calculated measures Show Values As and Quick Measures Create calculated tables Explore your time-based data Introduction to DAX DAX calculation types DAX functions Visualizations Introduction to visuals in Power BI Create and customize simple visualizations Modify colors in charts and visuals Shapes, text boxes, and images Page layout and formatting Group interactions among visualizations Visual hierarchies and drill-down Using custom visualizations Create a KPI Visualization Geo-Data and Maps Reports, Publishing and Sharing Introduction to the Power BI service Quick insights in Power BI Create and configure a dashboard Ask questions of your data with natural language Create custom Q&A suggestions Share dashboards with your organization Introduction to content packs, security, and groups Publish Power BI Desktop reports Print and export dashboards and reports Create groups in Power BI Use content packs Update content packs Publish to web Who is this course for? Who is this course for? This course facilitates you with knowledge on the potential for Power BI Desktop to analyse and connect to different sources of data, creating Relationships between those different datasets, Query the data using Shaping and data Modelling, and to create Visualisations, and publish Reports to different platforms. Requirements Requirements Before attending this course, delegates should have: - A general knowledge of database concepts (fields, records and relationships) - Familiarity with Excel. Career path Career path Business Intelligence Data Analysis ETL & Data Warehousing

Build your Power BI skills fast on this 1-day introduction to Power BI training course. This is a hands-on course. We give you plenty of time to play with what you are being taught and ask questions. Our expert instructors break the course into easily digestible sections so that we can make sure that no-one is left behind. By the time you finish, you’ll be a comfortable, capable Power BI user.  ✔ A complete introduction to Power BI.  ✔ Plenty of time to ask questions and one-to-one attention.  ✔ Friendly expert trainers who make sure no-one is left behind.  ✔ All the materials and extras that you’ll ever need.  ✔ Ongoing support for 6 months after the course. Our courses are delivered in Guildford, London, Online, or even on-site at your offices!

In today's fast-changing competitive environment, people in all roles need to have more commercial awareness and responsibility.

Drive improvement with our one-day Process Mapping workshop. Our Process Mapping Training course has been designed as a one-day programme so that your business may use Process Mapping as THE TOOL to drive improvement. The techniques explained in this practical "hands-on" workshop will yield real, timely, and motivating results. A process map is a visual tool used to illustrate your core processes. It is essentially a breakdown of a process to determine how it flows and, ultimately, how effective it is. Those who use PROCESS MAPPING look closely at elements such as the structure of a system and the flow of communication within the system. It is therefore a communication tool, a planning tool, and a tool to drive unnecessary waste and cost out of your organisation. It is also a practical tool to help you identify and address core problems in your organisation. PROCESS MAPPING is an essential and critical stage in the search for performance improvement. Yet the approach is not widely recognized or understood. PROCESS MAPPING will help managers and staff alike discover what the process is currently like, what are the Value Added, the Non-value Added, and the Value Enabling activities, and how to identify opportunities for improvement as you map out how the process should look like Whether delivering a service or producing a product, successful organisations are in continual pursuit of better, faster and cheaper way of delivering satisfaction to their customers. PROCESS MAPPING will provide organizations with an agreed and accurate understanding of their current processes, and will therefore provide new sources of rich stimulation for ideas to solve problems, find improvements, and map what the process should look like. It is therefore a foundation upon which many organizations then develop and implement many other Lean tools. PROCESS MAPPING is also a key tool used in the design and implementation of a robust Quality Operating System. The International Organization for Standardization or ISO 9001 encourages a process approach to quality management as it helps in the understanding of how each process relates to other processes within the organization and how those interactions impact Quality Management. This workshop can also be delivered in-house as a stand-alone training workshop or integrated into wider improvement activities. We are happy to discuss Process Mapping in the context of your own business needs, so please contact us via email at compete@cforc.org or phone +44 (0)28 9073 7950 or our Dublin office +353 8 7224 2575 for more information.

Machine literacy in data wisdom is a fleetly expanding discipline and now is the crucial element. This groundbreaking field equips computers and systems with the capacity to learn from data and ameliorate their performance over time without unequivocal programming. Statistical ways are employed to train algorithms to produce groups or prognostications and to find significant findings in data mining systems. immaculately, the conclusions made from these perceptivity impact crucial growth pointers in operations and companies. What's Machine Learning? . Machine learning classes in pune The machine literacy term was chased by Arthur Samuel in 1959. It's the discipline solely concentrated on studying and erecting tools and ways that can let machines learn. These styles use data to enhance the computer performance of a particular set of tasks. Machine literacy algorithms induce prognostications or possibilities and produce a model grounded on data samples, also called training data. There's a need for machine literacy as these algorithms are applied in a broad range of operations, for illustration, computer vision, dispatch filtering, speech recognition, husbandry, and drugs, where it's a challenge to produce traditional algorithms that can negotiate the needed tasks. orders in Machine Learning Being such a vast and complicated field, machine literacy is divided into three different orders machine literacy orders Supervised literacy – In this system, the algorithm is trained using data that has been labeled and in which the target variable or asked result is known. Once trained, the algorithm may make prognostications grounded on unidentified information by learning how to associate input variables with the willed affair. Unsupervised literacy – In this case, the algorithm is trained on unlabeled data, and its thing is to discover structures or patterns within the data without having a specific target variable in mind. Common unsupervised literacy tasks include dimensionality reduction and clustering. underpinning literacy – An algorithm is trained via relations with the terrain in this type of literacy. The algorithm learns how to operate in order to maximize a price signal or negotiate a particular ideal. Through prices or penalties, it receives feedback that helps it upgrade its decision-making process. Artificial Intelligence and Machine Learning Artificial intelligence( AI) is divided into several subfields, and machine literacy( ML) is one of them. In order to produce intelligent machines that can pretend mortal intelligence, a variety of methodologies, approaches, and technologies are used. This notion is known as artificial intelligence( AI). The development of ways and models that allow computers to acquire knowledge from data and make recommendations or judgments without unequivocal programming is the focus of machine literacy( ML). Some academics were interested in the idea of having machines learn from data in the early stages of AI as an academic field. They tried to approach the issue using colorful emblematic ways and neural networks. They were primarily perceptrons, along with other models that were ultimately discovered to be reimaginings of the generalized direct models of statistics. For this case, you aim to make a system secerning cows and tykes. With the AI approach, you'll use ways to make a system that can understand the images with the help of specific features and rules you define. Machine literacy models will bear training using a particular dataset of pre-defined images. You need to give numerous farmlands of cows and tykes with corresponding markers. Why is Machine Learning Important? Machine literacy is an abecedarian subfield of artificial intelligence that focuses on assaying and interpreting patterns and structures in data. It enables logic, literacy, and decision-making outside of mortal commerce. The significance of machine literacy is expanding due to the extensively more expansive and more varied data sets, the availability and affordability of computational power, and the availability of high-speed internet. It facilitates the creation of new products and provides companies with a picture of trends in consumer geste and commercial functional patterns. Machine literacy is a high element of the business operations of numerous top enterprises, like Facebook, Google, and Uber. Prophetic Analytics Machine learning course in pune Machine literacy makes prophetic analytics possible by using data to read unborn results. It's salutary in the fields of finance, healthcare, marketing, and logistics. Associations may prognosticate customer growth, spot possible troubles, streamline operations, and take visionary action to ameliorate results using prophetic models. Personalization and recommendation systems Machine literacy makes recommendation systems and substantiated gests possible, impacting every aspect of our diurnal lives. Platforms like Netflix, Amazon, and Spotify use machine literacy algorithms to comprehend stoner preferences and offer substantiated recommendations. Personalization boosts stoner pleasure and engagement while promoting business expansion. Image and speech recognition Algorithms for machine literacy are particularly good at jobs like speech and picture recognition. Deep literacy, a branch of ML, has converted computer vision and natural language processing. It makes it possible for machines to comprehend, dissect, and produce visual and audio input. This technology is helpful for driverless vehicles, surveillance, medical imaging, and availability tools, among other effects. Machine learning training in pune

Data analysis translates numbers and data into information that can be used to solve problems or track business performance. Data analysis produces graphs, charts, tables and reports. Data analysis is in high demand across all sectors, such as finance, consulting, manufacturing, pharmaceuticals, government and education. The ability to pay attention to detail, communicate well and be highly organised are essential skills for data analysts. They not only need to understand the data but be able to provide insight and analysis through clear visual, written and verbal communication. This course provides the knowledge and skills to help you hone your data analysis skills.