business intelligence tools power bi quotation

“Power BI Desktop unifies the former Excel Power Tools (Power Pivot, Power Query and Power View) into one vastly improved, stand-alone, data discovery desktop application built on a modernized HTML5 visualization framework.”

It does not appear that I can just create a data entry field in Power BI with the rate I would like to offer and have that rate override the rates in the Rate Plan table. Seems like if I want to do that, I would need to create my tool in Excel. My thought to do the same in Power BI is to create a DAX table or measure that applies a discount to the rate or adds to the rate in increments of $0.0001 and add this as a slicer or filter. It would have to run on each region idependently. So, one slicer or filter within a visual per region.

A major driver in the uptick of M&A and venture activity are cloud warehouses likeAmazon Redshift, Google BigQuery and Snowflake. They have brought down the cost and complexity to build a data platform, in a shift away from Hadoop, with BI tools as the catalyst to make data exploration and visualization available to a much wider audience.

There’s a bit of confusion on how these tools work and their use cases. So in this post, we’re helping you find the answers, by looking at the current BI tool landscape and their differentiators.

BI tools facilitate exploration and visualization of data, and for the purpose of this post, we’re only including tools that support the major data warehouse (Amazon Redshift, Snowflake, Google BigQuery, Azure SQL Data Warehouse.)

Commercial – “Legacy”. Tools in this category offer an installable version of their product or a SaaS subscription. The key point though is that they ingest data into their platform before analysis happens, i.e. they schedule and run an extract of the full data set from your cloud warehouse on a regular basis.

Commercial – “Modern”. Tools in this category query the data “where it lives”, i.e. in your data warehouse. Unlike the legacy tools, they don’t run an extract of your data set and query data on a scheduled or ad-hoc basis in your warehouse.

Redashis a simple and powerful BI tool, suitable for advanced users since you need to know SQL to work with it. Redash provides an interactive query editor for sharing both the dataset and the query that generated it.

Redash provides the most impressive list of data sources from all open source BI tools in our review. You can use almost any data source you can imagine, from CSV to Elasticsearch, and of course the major data warehouses likeAmazon Redshift, Snowflake and BigQuery. You can explore the full listhere.

Domois a powerful cloud-based BI tool with solid data visualization capabilities that integrates with multiple data sources, including spreadsheets, databases, social networks, and almost any other existing cloud or local software solutions.

Qlik Senseis a powerful BI solution. Its Associative Engine automatically finds relationships inside the data. This simplifies the study of data and allows easy combination of any data sources, no matter how large or complex they are, into a single view.

Qlik Sense lets you explore data at any level of detail you need, explore the shape of the data and pinpoint outliers. AI-powered insight suggestions will not allow any meaningful data to escape from you. Qlik Sense also provides an opportunity for you to dive into advanced analytics calculations from R and Python using simple clicks.

Qlik Insight Bot adds AI-powered conversational analytics capabilities to Qlik Sense. With it, you can receive comprehensive reports, ask questions and discover insights using natural language.

Power BI is a business intelligence tool from Microsoft with all the benefits that Microsoft services ecosystem provides. PowerBI connects with the company’s main products, such as MS Excel, Azure Cloud Service, and SQL Server.  Power BI is marked as a leader in Gartner’s Magic Quadrant for Analytics and Business Intelligence Platforms.

Power BI interface is simple and clear, it will be familiar to Windows users. Visualizations are created by drag-and-drop. All you need to create any graphics – click on the desired item and drag it to an empty space in the report.

Power BI supports plenty of ways to incorporate or import your data (streaming data, cloud services, excel spreadsheets and third-party connections) and provides a simple API for integration with your applications.

Looker introduces innovation in how to collaborate on BI projects. Each project or data analyses can be saved as aGit project. In this way, you can use the full power of modern version control systems when collaborating on data.

With Integrate.io, Looker users get all the tools they need to optimize their queries running on Amazon Redshift. For more info on how this feature works, visitintermix.io/looker.

Chartio provides two modes of work: drag-and-drop interactive mode or SQL mode. While its UI is quite powerful, it is not so easy for non-experienced users as UI of some other competitors. Chartio has built a visual version of SQL, which enables you to explore, transform and visualize data on the fly through a drag-and-drop interface.

With intermix.io, Chartio users get all the tools they need to optimize their queries running on Amazon Redshift. For more info on how this feature works, visitintegrate.io/chartio.

Periscope Datais one of the new tools for BI. It provides support for different data source connection and data preparation using SQL, Python, and R. It also allows to perform predictive analytics and unstructured data analysis (for example, during the natural language processing).

With intermix.io, Periscope Data users get all the tools they need to optimize their queries running on Amazon Redshift. For more info on how this feature works, visitintermix.io/periscope.

On the chart below, you can see the searching trends for 3 open source BI tools described in this article: Metabase, Apache Superset, and Redash. At the time of writing, the most popular tool is Metabase which is approximately 2 times more popular than its closest pursuer, Redash. Also, you can notice that while the popularity of Apache Superset and Redash remains on a relatively stable level, the popularity of Metabase started to grow in the last couple of months (at the time of writing).

As was mentioned earlier, “legacy” commercial BI tools include Tableau, Domo, Qlik, and PowerBI. Their search popularity on Google Trends is depicted in the graph below. Tableau is the undoubted leader here. Its popularity is substantially higher than all other instruments. PowerBI ranks second. Domo is a little bit more popular than Qlik, but the level is relatively the same. There is no vivid trend for any platform, with unexpected peaks due to one-time events (i.e. the Tableau acquisition by Salesforce). The stable (side) nature of trend for all of these tools emphasizes their matureness in BI world one more time.

The leader in the set of “Modern” BI tools is even more clear than in the set of “Legacy” tools. Looker is like a giant among them. To better understand the gap between these instruments remember that Google Trends displays the relative popularity. Now, Looker at the time of writing has 37 points, while Chartio, Mode, and Periscope Data have 2, 3, and 1 point respectively. Looker had a huge peak in popularity due to its acquisition by Google. The trend is not clear here for any of the instruments. They all remain at the same level.

In this article, we highlighted some of the most popular business intelligence tools. We split them into open source and commercial proposals. In turn, commercial tools were conditionally split into “legacy” and “modern”.

“Modern” BI tools have emerged relatively recently. These tools provide some new value for data users. In many aspects, they are very good and can be considered as worthy competitors to the “legacy giants”.

We briefly described features of each of the instruments as well as tried to measure their popularity and existing trends. We can say that regardless of the fact that there are a lot of BI tools nowadays, there is no “swiss knife”. In each case, a person or organization should consider their use case, estimate what and how they need, which resources are available and then decide which instrument will be the optimal choice.

In this blog, I’ll show you how to create a dynamic stock quote app in Power BI. This interesting technique came out from a post in the Enterprise DNA forum.

The member wanted to know how we go about starting with online data and pulling that into Power BI and then analyzing it from there instead of starting with what we typically do, which is an Excel file or a CSB file.

And so, I wanted to show you how to do this and how easy it is. It shows how powerful Power BI is in terms of web scraping and automated data poll capabilities.

Business intelligence (BI) tools help businesses collect, monitor, analyze, and predict future business conditions by understanding all of the company’s complex big data in one place.

While the platform is easy to use, it still provides users with powerful features such as predictive analytics and the ability to create custom dashboards.

Tableau needs no introduction. It is one of the most popular business intelligence tools available today. Organizations of all sizes use Tableau to make informed decisions and improve their overall performance.

Plus, the Tableau Prep feature can help you clean, combine, and prepare data at a faster pace. It comprises of two tools – namely Tableau Prep Builder and Tableau Prep Conductor.

Predictive Analytics – It leverages machine learning to predict future trends based on your data. It also comes equipped with pre-built algorithms and ML model management tools.

Power BI is a web-based BI tool that helps you find and share actionable insights using data visualization. It also provides built-in AI tools, Excel integration, and custom data connectors.

If you want to learn more about Power BI and how it stacks up against one of its direct competitors, check out this review article on Power BI vs. Tableau.

Power Query –It enables data shaping and cleansing easily. You can rename the column, merge data, replace values, and modify other business-critical aspects of the data.

Augmented Analytics – It delivers AI-powered augmented analytics for smarter data preparation and discovering more accurate results. It also leverages natural language processing (NLP) to enable conversational-style answers and analytics.

Additionally, BI tools help the management visualize the relation among different data sets, make data-driven decisions, and deploy resources more optimally.

Thus, BI tools come equipped with cutting-edge technologies that reduce the complexities related to business intelligence and prepare, analyze, report and share data with multiple sources.

The right reporting tools allow data analysts to use online analytical processing to improve business performance and provide actionable business insights to decision-makers.

With the big data analytics market likely to reach $103 billion by 2023, it’s important to start harnessing the power of cloud data and advanced analytics.

The good news is that all of these BI tools offer easy-to-install business intelligence capabilities, including data augmentation, reporting, visualization, and more.

For instance, Domo and Microsoft Power BI are best for large enterprises requiring intricate reporting capabilities. On the other hand, Looker is a suitable BI tool to track customer actions and enhance sales for ecommerce businesses.

Some find it too complicated to use and are intimidated by the format. I have not been able to find training for management on how to use a report that someone else with PowerBI skills created.

A detailed article on Epicor reporting in Power BI (or any SSBI package) that quickly eliminates gaps that are prevalent with the standard available reports.

“Different verticals need different terminal retention rates for them to have successful businesses. If you’re on e-commerce and you’re retaining on a monthly active basis, like 20 to 30% of your users, you’re going to do very well. If you’re on social media, and the first batch of people signing up to your product are not like, 80% retained, you’re not going to have a massive social media site. [...] What you need to do is have the tools to think, ‘who out there is comparable’ and how you can look at it and say, ‘am I anywhere close to what real success looks like in this vertical?’”

“If an Internet company could obsess about only one metric, it should be conversion. No other metric so holistically captures as many critical aspects of a web site – user design, usability, performance, convenience, ad effectiveness, net promoter score, customer satisfaction – all in a single measurement. Yet despite the remarkable power of this metric, it is alarming how few companies today truly understand conversion and how to optimize it. As such, it is time to pound the table again – conversion is by far the most powerful Internet metric of all.”

“In a marketing analytics worldview, companies must have an accounting of and insight into all of their marketing programs in all of their channels, including web/browser, mobile apps, TV/video, social, paid media, field, print, outdoor and others. If your organization is still stuck in the web analytics mindset, it is time to reinvent your analytics practice, leveraging all of the available marketing analytics tools to make faster and better decisions and drive your business.”

iTech Analytic Solutions (iTAS)” is a leading MIS Reporting, Business Analytics, Data Analytics & Data Science training institute contributing towards the requirement of current IT & NON-IT industries. iTAS offers training on Tools ...Read more