How to use Microsoft Power BI

August 3, 2023 Coin Telegraph

Learn how Power BI unlocks the potential of your data and is useful for data visualization and analysis.

https://docs.google.com/document/d/1U8Kh-BgDD575lb3Mj3Xyqjd8_F8x65-gQ_muiys5up8/edit (piks for this article are in this doc)

In today’s data-driven world, organizations of all sizes are inundated with vast amounts of information. Extracting actionable insights from this data can be overwhelming and time-consuming.

Microsoft Power BI is a powerful business intelligence tool that empowers users to transform raw data into meaningful visualizations and interactive reports. In this article, we will delve into the basics of Microsoft Power BI and guide you through the process of harnessing its capabilities to unlock the full potential of your data.

Understanding Microsoft Power BI

A cloud-based business analytics application, Microsoft Power BI is made to connect, process and visualize data rapidly and effectively. It provides a user-friendly interface that enables data manipulation for both expert and non-technical users without the need for complex coding knowledge. The tool is a popular option for organizations all around the world because of its smooth connection with other Microsoft products, such as Excel and Azure.

In Power BI Desktop, there are three views available to users:

Report view: Users can utilize their custom queries to construct visually appealing representations, arrange them as desired, and create multi-page reports that can be shared with others.
Data view: This view provides a display of the report data in a data model format. Users can add measures, create new columns, and manage relationships between data elements.
Model view: Users can access a graphical representation of the established relationships in the data model. Additionally, they have the option to manage and modify these relationships as necessary.

Getting started with Power BI

Data source connection

The first step is to connect Power BI to your data sources. It supports various data sources, including Excel spreadsheets, databases, cloud services and online platforms, such as Google Analytics. Once connected, Power BI will automatically refresh the data to ensure your reports are always up-to-date.

Data transformation and modeling

One might need to tidy up and format the data before they can visualize it. One can easily filter, sort, pivot and merge data tables using Power BI’s Power Query Editor. One can also create connections between various tables using the Data Modeling tool to facilitate in-depth research.

Creating interactive reports and dashboards using Power BI

Data visualization

With the data ready, Power BI’s rich collection of data visualization tools comes into play. One can create compelling charts, graphs, maps and tables that represent complex data in a comprehensible manner. The extensive library of customizable visuals ensures one finds the perfect representation for specific needs.

Building dashboards

Power BI dashboards are user-friendly one-page displays of visualizations and reports. One can combine different visual elements to create a holistic view of the data, making it easy to monitor key performance indicators (KPIs) and track business metrics in real-time.

Report publishing and sharing

After creating insightful reports and dashboards, one can publish them to the Power BI service. This cloud-based sharing platform allows users to securely share visualizations with colleagues, stakeholders or clients. Moreover, one can set up automatic data refresh schedules to keep the reports up-to-date.

Power BI’s advanced features and data analysis capabilities

Data analysis expressions

The data analysis expressions (DAX) language is a powerful formula language used in Power BI for data manipulation and calculations. By mastering DAX, one can create complex measures, calculated columns and tables that go beyond the built-in aggregation functions.

Additionally, DAX queries can be generated and executed using various tools, including SQL Server Management Studio (SSMS) and open-source applications, such as DAX Studio. Unlike DAX calculation formulas, which are limited to tabular data models, DAX queries can also be executed against Analysis Services Multidimensional models. DAX queries are commonly preferred due to their ease of writing and higher efficiency compared to Multidimensional Data Expressions (MDX) queries.

A DAX query resembles a statement, similar to a SELECT statement in T-SQL. The simplest form of a DAX query is an “evaluate” statement, as shown in the example below:

Power BI mobile app

Power BI’s mobile app extends the functionality to smartphones and tablets, enabling access to reports and dashboards on the go. Stay connected to the data and receive timely insights, regardless of the location.

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Covalent CEO: There’s an ‘unresolved backlog’ of unfilled Web3 data roles

October 4, 2022 Coin Telegraph

Blockchain Analytics

The demand for on-chain analysts is set to further increase with Web3 data outgrowing Web2 data over the next 20-30 years, says Covalent's Ganesh Swami.

Ganesh Swami, CEO of blockchain data aggregator Covalent says there continues to be an “intense demand” for on-chain data analysts, that is yet to be satisfied.

Speaking to Cointelegraph, Swami said that analysts are in “intense demand” as there’s a “real need” for data experts to “make sense” of on-chain data, explaining:

“There is an unresolved backlog of unfilled data-driven roles. This demand is a testament to how eager blockchain and non-blockchain companies alike are to make sense of their own and competitors’ on-chain data.”

Swami explained that while the demand for on-chain data analysts has yet to eclipse their Web2 counterpart, the growth of stablecoin usage, lending, and decentralized finance (DeFi) products over the last 18 months has led to increasing demand for the job title.

Swami said similar to data analysts in traditional industries, on-chain data analysts can expect to analyze a company's “reach, retention and revenue” metrics, except, in this case, the intelligence would be found on-chain data across multiple blockchains.

For example, in the case of an NFT project, Swami explained that "reach" would look into “how many people mint your tokens” and "retention" would relate to “what is the average holding period for these tokens" which is important to know whether investors are using these for “quick flips” or “holding on to them” long term.

"Revenue" is about sales — with blockchain analysts able to determine whether the sales are “concentrated through a handful of sales or distributed across multiple collections," he explained.

But the role doesn't e there. Swami said that “to make better protocols and better serve users,” on-chain analysts can “cross-target users for marketing purposes or for user acquisition purposes” by reviewing what’s happened on competitor protocols, as the blockchain leaves what Swami likes to call “historical breadcrumbs.”

Swami also predicted that “Web3 data will exceed Web2 data” at some point in the next 20-30 years, and that Web3 data analysis “will be much, much bigger than the current business intelligence market, which is currently worth hundreds of billions of dollars.”

Addressing the current deficit of on-chain analysts, Covalent is set to launch a four-week “Data Alchemist Boot-Camp” on Oct. 19, which aims to train over 1,000 individuals in on-chain analytics.

“The only prerequisite to joining our Data Alchemist Boot-Camp is a desire to learn about Web3; come with that, and we’ll pay you to learn,” said Swami.

Over the near term, however, Swami said on-chain analysts will likely find more job opportunities in Web2 companies which are entering Web3, rather than Web3 native projects themselves:

“It will be faster and better for a Web2 company with their hundreds of millions of players or users to add over Web3 experiences, and what we can see, immediately what we have a line of sight to is Web2 businesses, adding a Web3 experience.”

“Companies such as Adidas and Samsung also now have departments of metaverse data scientists and analysts to serve the dashboards and metrics management,” he added.

Business Intelligence