Cepta The Future of Data with Power BI

Power BI is a business analytics service that enables you to see all of your data through a single pane of glass. Live Power BI dashboards and reports...

It covers very basic knowledge on following : 1) What is Power BI 2) What is Data Visualization 3) Why Data Visualization

BI: new of the buzz words that everyone is talking about but what is it? How can it be used to make a impact in my organization? How do I get started? In this session, we will talk about it and show you a live example in Office 365's SharePoint Online. Objectives/Outcomes: In this session, participants will learn: 1. What is BI 2. What is Microsoft's Power BI 3. Case Studies 4. How can I get it

Power BI is a self-service business intelligence tool that allows users to analyze data and create reports and visualizations. It includes components for data discovery, analysis, and visualization both on-premises using Excel and in the cloud using the Power BI service. The tool integrates with Office 365 and allows users to discover, visualize, and share insights from data.

( Power BI Training - https://www.edureka.co/power-bi-training ) This Edureka videoon "Power BI Tutorial" will provide you with the fundamental knowledge on Power BI (Blog: https://goo.gl/uFTDU3). Below are the topics covered in this tutorial: 1. Why do we need Business Intelligence? 2. What is Self Service Business Intelligence? 3. Why Power BI? 4. What is Power BI? 5. Demo: Report and Dashboard Creation

Business intelligence dashboards and data visualizations serve as a launching point for better business decision making. Learn how you can leverage Power BI to easily build reports and dashboards with interactive visualizations.

Explain about power BI Overview from Power BI Desktop, Power BI Service, Power BI Report Server and Power BI Mobile that consume all BI Data from Dataset and datamodel

Microsoft Power BI Overview What is Power BI? Microsoft Power BI Benefits What powers Power BI in Office 365? Power BI Security Market Position

Power BI Dashboard in an hour with Various Slides. Target Audience: Useful for Develops and DBA those who want to know what is Power BI and How we can utilize various features. Also session will be useful for anyone who wants learn Power BI from basic. Abstract: In this session, We will walk through various features of Power BI, How Power BI can transform your company’s data into rich visuals and Easy yet powerful Analytics solutions for your whole organization. At end of session with following Power BI Dashboard example sp_Blitz in Dashboard SQL Server Info Dashboard Twitter Dashboard World Dashboard Most important takeaways from session – You will be learning basics of Power BI with the additional perk of analyzing sp_Blitz in Power BI. Various features of Power BI making you from ZERO to HERO After this session, you will be able to analyze data into Power BI

This Edureka tutorial on "Getting started with Power BI" will provide you the fundamental knowledge of Power BI. Below are the topics covered in this tutorial: 1. What is Self Service Business Intelligence? 2. Why Power BI? 3. What is Power BI? 4. Demo on Power BI

This slide deck explains in a comprehensive way what Power BI is, how the Power BI architecture looks like and what the usage scenarios are for using Power BI and related tools

This Edureka Power BI Dashboard Tutorial will take you through step by step creation of Power BI dashboard. It helps you learn different functionalities present in Power BI tool with a demo on superstore dataset. You will learn how to create a Power BI dashboard by taking out multiple insights from superstore dataset and representing them visually.

Presented to The Ottawa IT Community Meetup Group (Ottawa SQL - PASS Chapter) on Thursday September 19 Powerful Self-Service BI in Excel 2013 - Data search and discovery with Power Query (formerly "Data Explorer"), analyzing and modeling with Power Pivot, visualizing and exploring with Power View and Power Map (formerly codename "GeoFlow")

Power BI consists of several components for data transformation, modeling, visualization, and natural language querying. Power Query is used to connect to data sources, clean the data, and publish to Power BI or Excel. Power Pivot is an in-memory data modeling tool using DAX. Power View enables creation of reports and visualizations. Power Map visualizes geospatial data in 3D. Power BI Desktop is a development tool and Power Q&A allows natural language questions over published models.

New features in Power BI give it enterprise tools, but that does not mean it automatically creates an enterprise solution.  In this talk we will cover these new features (composite models, aggregations tables, dataflow) as well as Azure Data Lake Store Gen2, and describe the use cases and products of an individual, departmental, and enterprise big data solution.  We will also talk about why a data warehouse and cubes still should be part of an enterprise solution, and how a data lake should be organized.

This document discusses Power BI, a Microsoft tool for data visualization and analytics. It covers what Power BI is, its components like Power Query, Power Pivot, and Power View. It also discusses the building blocks of Power BI like datasets, reports, dashboards and tiles. The document demonstrates how to install Power BI and introduces some key concepts like DAX and different types of visualizations. It aims to provide an overview of Power BI, its capabilities and how to use some of its main features.

This document provides an overview and instructions for attending a "Dashboard in a Day" workshop on Microsoft Power BI. It includes prerequisites for the workshop, such as having a computer that meets minimum system requirements and having a Power BI account. The agenda outlines the topics to be covered, including introductions, building reports and dashboards in Power BI Desktop and the Power BI service, and opportunities for questions. Resources are provided on connecting to the workshop wireless network and engaging with the broader Power BI community.

Dans cette session nous vous présenterons les différentes manières d'utiliser SQL Server dans une infrastructure Cloud (Microsoft Azure). Seront présentés des scénarios hybrides, de migration, de backup, et d'hébergement de bases de données SQL Server en mode IaaS ou PaaS.

This document provides an overview of a course on implementing a modern data platform architecture using Azure services. The course objectives are to understand cloud and big data concepts, the role of Azure data services in a modern data platform, and how to implement a reference architecture using Azure data services. The course will provide an ARM template for a data platform solution that can address most data challenges.

Slides of the presentation by Heather Grandy at C# Corner Toronto chapter Feb 2019 meetup on Azure Databricks Spark

The document discusses Azure SQL Database Managed Instance, a new fully managed database service that provides SQL Server compatibility. It offers seamless migration of SQL Server workloads to the cloud with full compatibility, isolation, security and manageability. Customers can realize up to a 406% ROI over on-premises solutions through lower TCO, automatic management and scaling capabilities.

Webinar presentation deck for Azure Synapse. 100 level Presentation to provide overview of Synapse, capabilities etc.

In dieser Session stellen wir ein Projekt vor, in welchem wir ein umfassendes BI-System mit Hilfe von Azure Blob Storage, Azure SQL, Azure Logic Apps und Azure Analysis Services für und in der Azure Cloud aufgebaut haben. Wir berichten über die Herausforderungen, wie wir diese gelöst haben und welche Learnings und Best Practices wir mitgenommen haben.

Technical introduction of Microsoft Azure, from IaaS to PaaS, Serverless, Container Services, DBaaS and Machine Learning.

Azure Data Factory is a fully managed data integration service in the cloud. It provides a graphical user interface for building data pipelines without coding. Pipelines can orchestrate data movement and transformations across hybrid and multi-cloud environments. Azure Data Factory supports incremental loading, on-demand Spark, and lifting SQL Server Integration Services packages to the cloud.

Azure provides cloud computing services including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS) that allow users to rapidly setup environments, scale resources to meet demands, and increase efficiency. Azure offers a wide range of services such as compute, storage, databases, analytics, machine learning, IoT, and security to help users migrate existing applications or build new cloud-native applications. The document outlines key scenarios for using Azure such as development/testing, lift and shift of existing applications, big data analytics, and identity management to provide a starting point for leveraging the cloud platform

Azure Data Lake Intro (SQLBits 2016 ADL/USQL Pre-Conference) Data Lake concept, Azure Data Lake, HDINSIGHT, Azure Data Lake Storage and Analytics

So you got a handle on what Big Data is and how you can use it to find business value in your data.  Now you need an understanding of the Microsoft products that can be used to create a Big Data solution.  Microsoft has many pieces of the puzzle and in this presentation I will show how they fit together.  How does Microsoft enhance and add value to Big Data?  From collecting data, transforming it, storing it, to visualizing it, I will show you Microsoft’s solutions for every step of the way

Azure SQL Database now has a Managed Instance, for near 100% compatibility for lifting-and-shifting applications running on Microsoft SQL Server to Azure. Contact me for more information.

Part 1 of a conference workshop. This forms the morning session, which looks at moving from Business Intelligence to Analytics. Topics Covered: Azure Data Explorer, Azure Data Factory, Azure Synapse Analytics, Event Hubs, HDInsight, Big Data

This document discusses ETL patterns in the cloud using Azure Data Factory. It covers topics like ETL vs ELT, the importance of scale and flexible schemas in cloud ETL, and how Azure Data Factory supports workflows, templates, and integration with on-premises and cloud data. It also provides examples of nightly ETL data flows, handling schema drift, loading dimensional models, and data science scenarios using Azure data services.

The breath and depth of Azure products that fall under the AI and ML umbrella can be difficult to follow. In this presentation I’ll first define exactly what AI, ML, and deep learning is, and then go over the various Microsoft AI and ML products and their use cases.

The document discusses Azure Data Factory and its capabilities for cloud-first data integration and transformation. ADF allows orchestrating data movement and transforming data at scale across hybrid and multi-cloud environments using a visual, code-free interface. It provides serverless scalability without infrastructure to manage along with capabilities for lifting and running SQL Server Integration Services packages in Azure.

The new Microsoft Azure SQL Data Warehouse (SQL DW) is an elastic data warehouse-as-a-service and is a Massively Parallel Processing (MPP) solution for "big data" with true enterprise class features. The SQL DW service is built for data warehouse workloads from a few hundred gigabytes to petabytes of data with truly unique features like disaggregated compute and storage allowing for customers to be able to utilize the service to match their needs. In this presentation, we take an in-depth look at implementing a SQL DW, elastic scale (grow, shrink, and pause), and hybrid data clouds with Hadoop integration via Polybase allowing for a true SQL experience across structured and unstructured data.

This document provides an overview of 6 modules related to SQL Server workshops: - Module 1 covers database design and architecture sessions - Module 2 focuses on intelligent query processing, data classification/auditing, database recovery, data virtualization, and replication capabilities - Module 3 discusses the big data landscape, including data growth drivers, common use cases, and scale-out processing approaches like Hadoop and Spark

Azure Machine Learning Services provides an end-to-end, scalable platform for operationalizing machine learning models. It allows users to deploy models everywhere from containers and Kubernetes to SQL Datawarehouse and Cosmos DB. It also offers tools to boost data science productivity, increase experimentation, and automate model retraining. The platform seamlessly integrates with Azure services and is built to deploy models globally at scale with high availability and low latency.

This document summarizes how businesses can transform through business intelligence (BI) and advanced analytics using Microsoft's modern BI platform. It outlines the Power BI and Azure Analysis Services tools for visualization, data modeling, and analytics. It also discusses how Collective Intelligence and Microsoft can help customers accelerate their move to a data-driven culture and realize benefits like increased productivity and cost savings by implementing BI and advanced analytics solutions in the cloud. The presentation includes demonstrations of Power BI and Azure Analysis Services.

Redgate Summit Atlanta Presentation on AI, the economic downturn and surviving as a technical professional.

This are my keynote slides from SQL Saturday Oregon 2023 on AI and the Intersection of AI, Machine Learning and Economnic Challenges as a Technical Specialist

This document discusses migrating high IO SQL Server workloads to Azure. It begins by explaining that every company has at least one "whale" workload that requires high CPU, memory and IO. These whales can be challenging to move to the cloud. The document then provides tips on determining if a workload's issue is truly high IO or caused by another factor. It discusses various wait events that may indicate IO problems and tools for monitoring IO performance. Finally, it covers some considerations for IO in the cloud.

This document provides an overview of options for running Oracle solutions on Microsoft Azure infrastructure as a service (IaaS). It discusses architectural considerations for high availability, disaster recovery, storage, licensing, and migrating workloads from Oracle Exadata. Key points covered include using Oracle Data Guard for replication and failover, storage options like Azure NetApp Files that can support Exadata workloads, and identifying databases that are not dependent on Exadata features for lift and shift to Azure IaaS. The document aims to help customers understand how to optimize their use of Oracle solutions when deploying to Azure.

This document provides guidance and best practices for migrating database workloads to infrastructure as a service (IaaS) in Microsoft Azure. It discusses choosing the appropriate virtual machine series and storage options to meet performance needs. The document emphasizes migrating the workload, not the hardware, and using cloud services to simplify management like automated patching and backup snapshots. It also recommends bringing existing monitoring and management tools to the cloud when possible rather than replacing them. The key takeaways are to understand the workload demands, choose optimal IaaS configurations, leverage cloud-enabled tools, and involve database experts when issues arise to address the root cause rather than just adding resources.

This document discusses strategies for managing ADHD as an adult. It begins by describing the three main types of ADHD - inattentive, hyperactive-impulsive, and combined. It then lists some of the biggest challenges of ADHD like executive dysfunction, disorganization, lack of attention, procrastination, and internal preoccupation. The document provides tips and strategies for overcoming each challenge through organization, scheduling, list-making, breaking large tasks into small ones, and using technology tools. It emphasizes finding accommodations that work for the individual and their specific ADHD presentation and challenges.

This document provides guidance and best practices for using Infrastructure as a Service (IaaS) on Microsoft Azure for database workloads. It discusses key differences between IaaS, Platform as a Service (PaaS), and Software as a Service (SaaS). The document also covers Azure-specific concepts like virtual machine series, availability zones, storage accounts, and redundancy options to help architects design cloud infrastructures that meet business requirements. Specialized configurations like constrained VMs and ultra disks are also presented along with strategies for ensuring high performance and availability of database workloads on Azure IaaS.

Kellyn Gorman shares her experience living with ADHD and strategies for turning it into a positive. She discusses how ADHD impacted her childhood and how it still presents challenges as an adult. However, with the right tools and understanding of her needs, she is able to find success. She provides tips for organizing, prioritizing tasks, managing distractions, and accessing support. The key is learning about ADHD and how to structure one's environment and routine to play to one's strengths rather than fighting against the condition.

Migrating Oracle workloads to Azure requires understanding the workload and hardware requirements. It is important to analyze the workload using the Automatic Workload Repository (AWR) report to accurately size infrastructure needs. The right virtual machine series and storage options must be selected to meet the identified input/output and capacity needs. Rather than moving existing hardware, the focus should be migrating the Oracle workload to take advantage of cloud capabilities while ensuring performance and high availability.

This document discusses overcoming silos when implementing DevOps for a new product at a company. The teams involved were dispersed globally and siloed in their tools and processes. Challenges included isolating workload sizes, choosing a Linux image, and team ownership issues. The solution involved aligning teams, automating deployment with Bash scripts called by Terraform and Azure DevOps, and evolving the automation. This improved communication, decreased teams from 120 people to 7, and increased deployments and profits for the successful project.

This document discusses best practices for migrating database workloads to Azure Infrastructure as a Service (IaaS). Some key points include: - Choosing the appropriate VM series like E or M series optimized for database workloads. - Using availability zones and geo-redundant storage for high availability and disaster recovery. - Sizing storage correctly based on the database's input/output needs and using premium SSDs where needed. - Migrating existing monitoring and management tools to the cloud to provide familiarity and automating tasks like backups, patching, and problem resolution.

This document provides an overview of how to successfully migrate Oracle workloads to Microsoft Azure. It begins with an introduction of the presenter and their experience. It then discusses why customers might want to migrate to the cloud and the different Azure database options available. The bulk of the document outlines the key steps in planning and executing an Oracle workload migration to Azure, including sizing, deployment, monitoring, backup strategies, and ensuring high availability. It emphasizes adapting architectures for the cloud rather than directly porting on-premises systems. The document concludes with recommendations around automation, education resources, and references for Oracle-Azure configurations.

Interactive Slide on Power BI Eco-System and where data should be secured with links on how to secure

This is the second session of the learning pathway at PASS Summit 2019, which is still a stand alone session to teach you how to write proper Linux BASH scripts

This document discusses techniques for optimizing Power BI performance. It recommends tracing queries using DAX Studio to identify slow queries and refresh times. Tracing tools like SQL Profiler and log files can provide insights into issues occurring in the data sources, Power BI layer, and across the network. Focusing on optimization by addressing wait times through a scientific process can help resolve long-term performance problems.

The document provides tips and tricks for scripting success on Linux. It begins with introducing the speaker and emphasizing that the session will focus on best practices for those already familiar with BASH scripting. It then details various tips across multiple areas: setting the shell and environment variables, adding headers and comments to scripts, validating input, implementing error handling and debugging, leveraging utilities like CRON for scheduling, and ensuring scripts continue running across sessions. The tips are meant to help authors write more readable, maintainable, and reliable scripts.

This document discusses connecting Oracle Analytics Cloud (OAC) Essbase data to Microsoft Power BI. It provides an overview of Power BI and OAC, describes various methods for connecting the two including using a REST API and exporting data to Excel or CSV files, and demonstrates some visualization capabilities in Power BI including trends over time. Key lessons learned are that data can be accessed across tools through various connections, analytics concepts are often similar between tools, and while partnerships exist between Microsoft and Oracle, integration between specific products like Power BI and OAC is still limited.

Mentors provide guidance and support, while sponsors use their influence to advocate for and promote a protege's career. Obtaining both mentors and sponsors is important for advancing in one's field and overcoming biases, yet women often have fewer sponsors than men. The document outlines strategies for how women can find and work with sponsors, and how men can act as allies in supporting women. Developing representation of women in technology fields through mentorship and sponsorship can help initiatives become self-sustaining over time.

Pass Summit 2018 presentation Use Case Story of customer work at Microsoft with Higher Ed Customers.

Kellyn Pot'Vin-Gorman presented on GDPR compliance. Some key points include: - GDPR went into effect in May 2018 and covers any data belonging to an EU citizen. - Fines for non-compliance can be up to 4% of annual revenue or €20 million. - DBAs play a role in identifying critical data, auditing processes, and reporting on compliance. - An AI tool assessed the privacy policies of 14 major companies and found they all failed to meet GDPR requirements. - Achieving compliance requires security frameworks, data mapping, encryption, access controls, and dedicated teams.

Manual Method of Product Research | Helium10 | MBS RETRIEVER

Is your patent a vanity piece of paper for your office wall? Or is it a reliable, defendable, assertable, property right? The difference is often quality. Is your patent simply a transactional cost and a large pile of legal bills for your startup? Or is it a leverageable asset worthy of attracting precious investment dollars, worth its cost in multiples of valuation? The difference is often quality. Is your patent application only good enough to get through the examination process? Or has it been crafted to stand the tests of time and varied audiences if you later need to assert that document against an infringer, find yourself litigating with it in an Article 3 Court at the hands of a judge and jury, God forbid, end up having to defend its validity at the PTAB, or even needing to use it to block pirated imports at the International Trade Commission? The difference is often quality. Quality will be our focus for a good chunk of the remainder of this season. What goes into a quality patent, and where possible, how do you get it without breaking the bank? ** Episode Overview ** In this first episode of our quality series, Kristen Hansen and the panel discuss: ⦿ What do we mean when we say patent quality? ⦿ Why is patent quality important? ⦿ How to balance quality and budget ⦿ The importance of searching, continuations, and draftsperson domain expertise ⦿ Very practical tips, tricks, examples, and Kristen’s Musts for drafting quality applications https://www.aurorapatents.com/patently-strategic-podcast.html

CIO Council Cal Poly Humboldt September 22, 2023

Cybersecurity is a major concern in today's connected digital world. Threats to organizations are constantly evolving and have the potential to compromise sensitive information, disrupt operations, and lead to significant financial losses. Traditional cybersecurity techniques often fall short against modern attackers. Therefore, advanced techniques for cyber security analysis and anomaly detection are essential for protecting digital assets. This blog explores these cutting-edge methods, providing a comprehensive overview of their application and importance.

Are you interested in dipping your toes in the cloud native observability waters, but as an engineer you are not sure where to get started with tracing problems through your microservices and application landscapes on Kubernetes? Then this is the session for you, where we take you on your first steps in an active open-source project that offers a buffet of languages, challenges, and opportunities for getting started with telemetry data. The project is called openTelemetry, but before diving into the specifics, we’ll start with de-mystifying key concepts and terms such as observability, telemetry, instrumentation, cardinality, percentile to lay a foundation. After understanding the nuts and bolts of observability and distributed traces, we’ll explore the openTelemetry community; its Special Interest Groups (SIGs), repositories, and how to become not only an end-user, but possibly a contributor.We will wrap up with an overview of the components in this project, such as the Collector, the OpenTelemetry protocol (OTLP), its APIs, and its SDKs. Attendees will leave with an understanding of key observability concepts, become grounded in distributed tracing terminology, be aware of the components of openTelemetry, and know how to take their first steps to an open-source contribution! Key Takeaways: Open source, vendor neutral instrumentation is an exciting new reality as the industry standardizes on openTelemetry for observability. OpenTelemetry is on a mission to enable effective observability by making high-quality, portable telemetry ubiquitous. The world of observability and monitoring today has a steep learning curve and in order to achieve ubiquity, the project would benefit from growing our contributor community.

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