Data, data, data... The day-to-day activity of companies generates a relentless volume of information (so-called Big Data) from multiple sources (web, ERP, CRM, apps, etc.) which must be analysed and all of the value extracted from it with maximum speed and precision in order to be competitive. Thus, the growing presence of data analytics and Business Intelligence software in organisations. Information is power.
In recent years, the role of data within organisations has changed substantially: from being a mere record of activity to becoming a strategic asset to generate income. In this transformation process, Data analytics tools have been fundamental.
Data analytics solutions examine datasets in millions of columns of complex data, their almost infinite combinations and possible interrelationships. From there, conclusions are drawn about the information they contain and patterns are discovered that can’t be seen by a human user.
The purpose of these tools is to offer information of added value which is very useful for decision making processes and for the constant adaptation of the business strategy to the market. To do this, algorithms of machine learning, automation and other advanced functionalities are integrated.
Some practical applications of Data Analytics in companies:
- Preventive maintenance and support. Data Analytics solutions enable companies who offer or carry out maintenance and support processes and services to be able to analyse their information (even in real time) to detect potential issues in parts/machines or the expiry of service licences. This information facilitates carrying out or anticipating maintenance to prevent accidents or costly production line closures, as well as promoting the renewal of service licences to customers.
- Optimisation of prices and fees. Data Analytics software facilitates the detection of prices of items with the best results in different conditions. It is possible to segment the client base and create models that show how many different types of customers want to pay specific amounts under specific circumstances. This is basic information for designing a pricing strategy.
- Tracking customers during the sales cycle. Many organisations use analytics tools to determine when a specific set of customers is ready to buy and when they are going to do so. This information is useful for the design of marketing campaigns and commercial actions.
- Improving customer service. Machine learning tools can already analyse the conversations between the sales team and customers. This information and the data analytics software provides a more accurate view of the customer’s concerns in order to offer them the best experience with a product/service/brand.
- Optimisation of production processes and the supply chain. Data analytics tools enable companies from the industrial sector to improve their manufacturing and logistics processes. For example, after analysing the data, they can discover the most common incidences and bottle necks, as well as the best time to produce orders, make shipments so they arrive on time and optimise their storage capacity.
Which data analytics tool do I need?
Storage, processing and analysis of data: Google BigQuery
A solution which is constantly increasing its presence in the market isGoogle BigQuery, a cloud storage platform (data warehousing) and data analytics on a large scale that integrates a query engine capable of processing terabytes of data in seconds and petabytes in minutes.
In a nutshell, it is a 100% cloud service from Google, without servers and fully scalable, which enables large volumes of information to be stored and processed, searchable through SQL queries.
It stands out for various reasons:
- Capacity to process data from different sources which are external or not from the Google environment. These sources include relational databases, cloud environments (Google Cloud Platform, AWS, Azure…), ERP solutions, CRM, Google Analytics, Internet of Things, Smartphone apps, etc. They can be combined with the queries that are performed subsequently.
- Storage in structured tables and columns. This characteristic facilitates queries to be performed and data analytics to be carried out using standard SQL, since it enables the data required for the query to be located quickly and optimise the use of resources.
- Ease of use. Google BigQuery works using standard SQL (Structured Query Language), one of the most widely used to extract information from relational databases. The queries are entered on a very intuitive console for the user. Once executed, the storage structure of the information in columns facilitates a fast achievement of results.
Thanks to its advanced integration capacities, Google BigQuery also enables queries to be built and executed, as well as its results to be viewed graphically in:
- Office tools such as Google Sheets or Microsoft Excel
- Advanced Business Intelligence solutions:Tableau,Looker, Google Data Studio, etc.
Analytical tools specialised in displaying data and BI: Tableau and Looker
They say a picture is worth more than a thousand words (i.e.. In this case, numbers!)… For many managers and users, it is necessary to view the information with added value to check the trends or patterns and make the best business decisions.
In this area, solutions like Tableau or Looker are fundamental. They have the capacity to represent this information in models, graphs and other visual resources in a question of seconds or minutes, giving users a more understandable version of the data. Let’s look at them a little closer!
- Tableau. This is a tool specialised in the visualisation of data and Business Intelligence capable of searching relational databases, spreadsheets, OLAP cubes, cloud databases, etc. It then turns this information into components of an interactive dashboard that the user can create according to their requirements, without needing knowledge of programming (simply dragging and dropping). It analyses millions of files in a few seconds.
- Looker. It is an advanced analytics platform that enables business metrics to be designed uniquely and consistently in all of the data sources, thereby creating a single source of the truth. As with the case of the previous tool, users can easily personalise and create interactive panels from the wide range of tables and graphs offered by the platform.
At Intelligence Partner, we have built up significant knowledge and experience indata analytics and Business Intelligence projects. We place all of this expertise at your disposal to help you to convert, with data analytics tools such as Big Query, Tableau or Looker, your Big Data into information with a high added value or, in other words, into an enormous competitive advantage for your business.
You just need to explain to us how your organisation currently handles its data and what your objectives are. We will study your case and suggest the best solution for your requirements, also showing you the benefits that it will give you.
Shall we start?