Google Business Intelligence Tools

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Google Business Intelligence Tools – In 2020, there are plenty of options when it comes to business intelligence tools that can confuse business buyers. There are an overwhelming number of factors to consider in choosing the platform that best suits your business needs.

Fortunately for you, we’ve gone through the trouble of evaluating four of the leading products on the market: Tableau, Microsoft Power BI, Google Data Studio, and IBM Cognos. These products are rated in three main categories: features, price and who they are for.

Google Business Intelligence Tools

For a single user, the price is $70 per month and is billed annually. That makes a bill of $840 per year. For the needs of teams or organizational collaboration, Tableau introduces three user types and allows you the freedom to create a mix of options that matches your business needs.

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Power BI offers two enterprise pricing plans: a free version and a paid ‘Pro’ version that costs $9.99 per user per month.

Interestingly, Google Data Studio is a completely free business intelligence tool to use and access. You’ll save dollars while still being able to access a relatively resourceful data system and share your reports with anyone.

Premium – This plan allows the solution to be deployed in a multi-tenant cloud architecture. It is priced at $70 per user per month and includes:

Enterprise – This plan includes all the features of Cognos Analytics, such as 500 GB of user storage and backups. Pricing is not publicly available, so you must contact IBM directly for a quote. Users can optionally purchase cloud capacity and an additional 250 GB of user storage.

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Arguably one of the most important features (besides visualization) of business intelligence tools is connecting to the data. Here are the highlights from each:

Visuals are great – but not if you can’t send it to others. Here’s where each stands:

Which Business Intelligence (BI) tools are right for your company? In 2020, there are plenty of options when it comes to business intelligence tools that can confuse business buyers… .vn

As a leading software developer in Vietnam, we have extensive experience in many fields, including e-commerce, car sharing, healthcare, Livestream and many more.

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Quality Outsourcing/Offshoring Company in Website/Mobile Apps, Blockchain Services, Artificial Intelligence – Big Data Services. Visit our website: https://.vnAs a technologist, I am always curious to discover and research innovative tools and technologies that can bring value to businesses and also help drive business decisions. I found Google’s Looker BI to be the leader in advanced data analysis and reporting for cloud organizations dealing with big data.

But for a self-taught student like myself, I need to first simplify the basic concepts behind business intelligence, what is the story, how does it work, what are the benefits, and then dig deeper into how Google’s Looker BI plays a key role in this.

I am hopeful that this article can be a good milestone in your exploration and journey towards business intelligence.

BI in its simplest form takes business data and presents it in user-friendly visualizations such as reports, dashboards, charts and graphs. It’s a technology that turns raw data into meaningful information to optimize performance and drive business decisions. BI encompasses the process of collecting data, storing data and analyzing data into meaningful information.

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Business Intelligence relies on data warehouses for its basic information. It uses fact-based and historical data to forecast, analyze market trends, understand your customers and help with business strategy. A database gathers data from multiple sources into one central system. Once the data is collected, it can support analysis and reporting using queries. It can further provide the user with results in the form of reports, graphs, charts and maps. Within BI, there are different technologies that can facilitate and analyze data such as OLAP (online analytical processing) or Hadoop. However, regardless of technology, BI will still need a data warehouse to work with.

Online Analytical Processing (OLAP) is a technology that supports multidimensional queries for complex and predictive analytics. It is a type of method that allows users to easily and selectively extract and query data to analyze it from different perspectives. OLAP provides trend analysis, financial reporting, sales forecasting, budgeting and other planning.

For example, a user can request that data be analyzed to display a spreadsheet showing the company’s sales for a given month in each state, compare revenue figures to another month, and see a comparison of sales from other states during the same period. .

Hadoop is also another technology that supports big data and analytics for BI. It is designed to process terabytes and even petabytes of unstructured and structured data. It divides large workloads into smaller blocks of data for faster processing. It is also open source software which makes it cheap for businesses to use, which is why it is also widely used.

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For example, Hadoop can make recommendations when a customer tries to buy a mobile phone, then it suggests a customer for the phone’s back cover and screen protector. Based on these suggestions, retailers can make the best decision that will help them improve their business and maximize their profits.

It can be argued that the history of BI predates the digital age, before computers and databases were introduced. But the first set of true BI vendors were established in the 1970s such as IBM, SAP and Siebel. These companies were among the first to develop comprehensive BI systems. Programs like Crystal Reports became essential for any manager looking for insightful business strategies.

Finally, in the early 2000s, more companies began to focus on BI, such as Microsoft, IBM, SAP, and Oracle. In 2010, cloud technology and web-based software came to life for real-time data analytics and improved visualization. In the current era of social media like Facebook and Twitter, a whole new range of big data was introduced. That’s why real-time data streaming and data warehousing and BI tools were now used in all industries.

Businesses move at the speed of light to stay competitive. To gain an advantage over competitors, you need to use data to make important decisions. Companies have a large amount of data that they can use to their advantage. BI plays an important role in taming this unstructured big data and presenting it visually in the form of insights and graphs. BI also helps increase productivity and ensure effective decision making.

The Next Evolution Of Looker, Your Unified Business Intelligence Platform

Google Looker is a cloud-based Business Intelligence tool that helps you explore, share and visualize data that drives better business decisions. Looker is a platform that allows you to create and share reports quickly and intelligently. It allows everyone in your organization to quickly analyze and gain insight into your data sets. Looker makes it incredibly easy to build a data exploration platform that makes your data accessible in meaningful, intuitive ways for your entire organization.

Unlike other traditional BI tools, Looker is cloud-based, bringing everything into your browsers and avoiding custom downloads. It also provides security settings to access your data. Looker was originally founded in 2012 and was later acquired by Google in 2019. It is now part of Google Cloud and powers part of Google’s Data Studio platform.

Looker is easy to use and you don’t need to download any desktop software as it is browser based. With all your data stored in the cloud, organizations can create and manage their own permissions and security much more easily and securely. With Looker, you don’t need to write any code.

Looker has a very large third-party ecosystem that you can use to extend it beyond just visualization software. It integrates with other major systems and tools such as Salesforce, Confluence, PowerPoint, AWS, Azure and on-premises databases.

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Looker can connect to several RDBMS systems, but not just cloud data stores. It can connect to Microsoft SQL Server, Azure SQL Database, MySQL, Amazon Redshift, Oracle SQL, PostGresSQL and Google BigQuery.

Looker lets you create easy-to-read reports and beautiful dashboards that help users explore various patterns in data. Using Looker, you can easily share rich photos anytime from any device.

LookML is a modeling language for describing dimensions, aggregates, calculations, and data relationships in an SQL database. Google Looker uses a model written in LookML to generate SQL queries to extract data against a given database. A LookML project is a collection of dashboard, model and view files. They are version controlled through a Git repository. LookML has several advantages and below are a few:

Most of the time, you extract raw data, prepare it, deliver an analysis, and then never use any of that work again. With LookML, once you define a dimension, you build on it, rather than rewriting it again.

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To make data good, you need to track what was changed and when, by whom and why. LookML provides version control using a Git repository.

LookML makes data knowledge accessible to everyone. Data scientists and developers can also enable non-technical users to build dashboards and complex metrics.

Looker is considered one of the best analytics platforms on the market by its users. Its data visualization capabilities make it easy for non-technical users who need real-time access to data that would otherwise require them to write SQL queries to

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