Running a business can be tricky if you fail to implement the correct business management tools. If your company deals with hundreds or thousands of customers, optimal productivity, budgeting and customer satisfaction should be at the top of your priority list. Achieving your company’s target goals can, however, be difficult if you’re unable to access all the relevant and useful data your business has.
While you may think that you understand the desires of your customers and the growth rate of your company, data-driven decision making is considered a more effective way to reach your goals. The use of big data analytics is, therefore, worth considering—as well as the services that have come from this concept, such as Google BigQuery.
What is big data?
Before diving into whether or not Google BigQuery is the future of big data analytics, it’s vital to firstly understand what “big data analytics” actually means. In the simplest of terms, the latter refers to a system that examines large bodies of data with the goal of uncovering trends, patterns, correlations and other helpful information. Big data is usually associated with high volume, high velocity and high variety information, and tends to deal with datasets that are too complex for other, more traditional data processing software.
What is big data used for?
Big data analytics can be used for multiple purposes while offering a wide range of advantages in comparison to other methods of reporting, tracking and management. If your company revolves around the manufacturing of goods or services, for example, big data can aid you in the development of your products. This can be done through the analysis of previous product success as well as the data collected from test markets and/or social groups that may dictate what commercial offerings are best received.
It’s important to note that in your attempts to gain further insight, your data may end up scattered across different apps and platforms. Certain big data systems can be used to automatically bring this information together (such as through the use of BigQuery integration).
Customer experience is another key area that can benefit from big data analytics. Gaining a better understanding of your target audience in order to effectively cater to them is crucial in this day and age. The collection and use of relevant metrics can, therefore, potentially boost your chances of engaging new prospects while keeping existing customers satisfied. Data on website visits, call logs and social media usage, for example, can all be maintained and utilized in hopes of better tailoring your content toward your desired clientele.
Enhanced security, affirmed compliance and fraud prevention are important areas of focus for any company, especially one doing business predominantly online. Fortunately for you, big data can also assist you with your fight against online hackers and internal breaches by identifying fraudulent activity and reporting it in a timely manner.
The operational side of your business could benefit greatly as well. With access to accurate information regarding production statuses, customer feedback and other supply and demand factors, you’ll most likely be better able to judge and maintain your company’s progress within the market.
Other uses may include:
- Maintenance checks
- Guides, resources, training and tutorials (all available in BigQuery documentation)
- Employee efficiency reviews
- Machine learning
- Innovation advancements through the examination of trends. (1)
Big data analytics advantages
There are several benefits to adopting data-analysis applications, including the following:
- Information gathered from a wide variety of sources
- Real-time data collection
- Faster and more effective decision making
- New products and service manufacturing
- Identification of security hacks or system failures
- Boosted company profits (cost-efficiency)
- Competitive pricing
- Timely responses to customer queries
- Optimized productivity. (2) (3)
What is Google BigQuery?
Google BigQuery is a service (within the Google Cloud platform (GCP)) implemented to collect and analyze big data (also known as a data warehouse). It was released in 2011 and praised for its serverless architecture that enables highly scalable and fast-provided structured query language (SQL) analytics. Through the use of Google’s existing infrastructure, users don’t need to fluster themselves with a database administrator, and can instead spend their time harnessing the insights and information the data has to offer. (4)
BigQuery, as a part of GCP, provides users with a substantial list of services and applications for managing data and workflow. Ingesting, storing, processing and visualizing information are key areas of focus that BigQuery aims to assist you with.
Advantages of using Google BigQuery may include:
- Independent scaling on demand
- Cost control and efficiency
- Timely data movement
- Real-time predictive analysis
- Easily shared insights
- Data protection
- Distribution management
- Software recovery
- High performance and durability
- Machine learning capabilities. (4) (5)
Is Google BigQuery the future of big data analytics?
Google has become well-known for their carefully constructed business tools. BigQuery is one of these systems, and its success is predominantly pegged to its vast and thorough capabilities. It can execute rapid ad-hoc queries in terabyte data sizes within a matter of seconds and petabyte data sizes within minutes across multiple datasets. Google BigQuery may represent the future of big data analytics due to the aforementioned architecture that facilitates optimal performance without the need for infrastructure management or the re-building of indices. (6)
Various influential companies, entrepreneurs and Google enthusiasts have adopted the Google BigQuery data warehouse and have praised its functionality and contribution to their business management. According to O’Reilly Media, for example, Twitter reported that they were able to democratize their data analysis and share company information with a wide variety of internal teams, using BigQuery. The Alpega Group were also able to optimize their innovation through the system, by utilizing real-time analytics that they’d previously failed to obtain. (6)
When managing a business, it can be easy to get flustered over some of the most basic functions and processes. Implementing big data analytics, especially through Google BigQuery, may be your knight in coded armor. The level of speed, storage and scalability should enable you to carry out tasks more efficiently without the hassle of having to create an infrastructure. If you’re looking for a cost-effective, diverse and easily usable data warehouse, Google BigQuery may be the way to go.
- “What is Big Data?” Source: https://www.oracle.com/au/big-data/what-is-big-data/#:~:text=Big%20data%20helps%20you%20identify,make%20regulatory%20reporting%20much%20faster.&text=Machine%20learning%20is%20a%20hot,machines%20instead%20of%20program%20them
- “Benefits and Advantages of Big Data & Analytics in Business,” Source: https://www.upgrad.com/blog/benefits-and-advantages-of-big-data-analytics-in-business/
- “Big Data Analytics – What is it and why it matter | SAS,” Source: https://www.sas.com/en_au/insights/analytics/big-data-analytics.html#:~:text=Big%20data%20analytics%20examines%20large,more%20traditional%20business%20intelligence%20solutions
- “New Blog Series – BigQuery Explained: An Overview,” Source: https://medium.com/google-cloud/bigquery-explained-overview-357055ecfda3
- “BigQuery,” Source: https://cloud.google.com/bigquery
- “Chapter 1. What Is Google BigQuery?” Source: https://www.oreilly.com/library/view/google-bigquery-the/9781492044451/ch01.html
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