Data Analytics Tools to Boost Your Business

Data Analytics Tools to Boost Your Business

By Veera Budhi for BusinessCloud

Veera Budhi, assistant VP for technology & services at Apexon, says business intelligence is critical for success in every business.

Companies that don’t understand the importance of data management are less likely to survive than those that do.

In fact, when it comes to business, your data is your most valuable asset. This is why business intelligence is so important for each and every organization.

If you’re analyzing the right data, you’ll be able to quickly understand which product is your most profitable. That knowledge will allow you to make smarter business decisions going forward.

Also, if having to find all the right data and analyzing it seems overwhelming, that’s understandable. A few years ago, if you wanted to find your most profitable product, you’d have to find and pull all the relevant data manually. Then you’d have to analyze the data yourself and put the report together.

That’s a time-consuming, expensive, labor-intensive project, and because of the nature of data, the resulting report would have a short shelf life. After all, as soon as the data changes, your previous report becomes obsolete.

Fortunately, tools for data analytics have improved in recent years, and there are lots of them. Some tools allow anyone — even someone who is intimidated by numbers, to pull data and run simple reports. Some produce sophisticated reports and data modeling but require data scientists. All of them allow organizations to run reports monthly, weekly, quarterly or whenever they need it.

What tool is right for your specific business? That will depend a lot on how many data sources you’re analyzing, how big your company is and the technology you’re already using.

There are many BI tools on the market, but here are our top five:

BigQuery

Google’s BigQuery is a unique data tool. Unlike the other offerings in this post, BiqQuery isn’t software you buy and then use to conduct an unlimited number of queries. Instead, it’s a web service that allows you to interactively analyze huge quantities of data, and you pay by the query.  If you run a report, you only pay for the processing time it took to create that report.

BigQuery is a great tool if you don’t want to manage your own data warehouse, or if you’re analyzing a lot of data and need the full force of Google’s computing power to run massive reports quickly. However, it isn’t available everywhere, and many of the features are still in beta.

Snowflake

Snowflake is a fully relational ANSI SQL data warehouse that allows you to leverage the skills and tools your organization already uses. Updates, removals, analytical functions, transactions and complex joins give you the full capabilities you need to make the most of your data.

Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. It is a true data warehouse-as-a-service running in the cloud. With built-in performance, there is no infrastructure to manage or knobs to turn. Snowflake automatically handles infrastructure, optimization, availability, data protection and more so you can focus on your data rather than managing it.

Tableau

Tableau is the biggest player in the data market, and it’s popular for good reason — it’s relatively easy to learn, offers excellent data visualization and has a variety of integrations.  Tableau plays well with a number of other platforms (it integrates with BigQuery for example, but it also integrates with non-analytic platforms like Slack or SalesForce), and can handle most types of data.

The drawback of Tableau is that the software doesn’t cope well if you’re trying to analyze data from more than three or four sources. If you’re trying to analyze Big Data, or several data sources, Tableau might not work for you. If you have only a few important data streams from external applications, however, Tableau might be your best bet.

Looker

Looker is a flexible BI tool that combines data modeling with data analytics. Essentially, Looker lives inside your database. Its modeling language, LookML, allows data teams to define the relationships in their database so that any users can work with your company’s data without having to know SQL, the language used to build relational databases. It also allows you to embed data modeling and analytics in your existing apps.

Looker offers a solid BI suite of features, but it is also fairly expensive. If you’re a smaller company, or on a budget, it might not be the right data tool for you.

Power BI

Power BI is Microsoft’s data analytics application. It comes included with many enterprise versions of Microsoft Office and allows users to visualize that data in dashboards. The dashboards are built using a drag and drop interface.

While Power BI can connect to a variety of external data sources, it really shines in a business that’s a Microsoft shop, because Power BI is built to handle data from Microsoft’s applications. If your organization uses Microsoft Office, you probably already have Power BI, so it’s a good tool to try if you want to get started with data analytics.

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