Best Business Analytics Tools Every Manager Should Know

Recently, so many tools and various software are being used to analyze and extract data in order to make beneficial information that can be accessed and used in many different ways. To get the best result, after connecting similar or correlated data, choosing the best tool and knowing how to use it is a major step. That is the main object of business analytics. Here are some of the business analytics tools that are used today in the business field:

1.     If having to choose between two or more different options, Business Experiments are the best. Business experiments, AB testing, and experimental design are basically comparing groups after implementing some changes on one of the groups and not on the other (the control group).

2.     Regression Analysis: If the company wants to understand what is the relationship between two variables, such as purchase and price, the company can use this statistical tool.

3.     Sentiment Analysis: Sentiment analysis is also known as opinion mining. This tool has the ability to define the behavior and attitude of the customer or a group of them combined. It gathers opinions from audio, video, or text data.

4.     Visual Analytics: When wanting to understand a large piece of data, visual analytics is considered the best tool due to its simplicity. It innovates a graph that holds similar paradigms. By that, it combines data analytics with data visualization.

5.     Data Mining: This is used usually in huge business companies. It is suitable for handling large data sets. The main activity done by this tool is connecting relative variables that have the same pattern, insight or relationship to promote the performance.

6.     Voice Analytics: Which is also known as speech analytics, is getting information and facts from conversations and audio recordings. How does this work? It can understand the words and phrases that are being said in the conversation. In addition to that, it can know the emotional content of the phrases. For that, it is used in determining complaints at the call center.  

7.     When extracting a piece of information through medical graphs, images or photographs, this is called Image Analytics. It is based on digital geometry and pattern recognition. This is best used for security purposes such as facial recognition.

8.     On the other hand, when gathering insights from videos, it is Video Analytics. This tool can do everything image analytics can handle, and above that, it tracks the behavior. It is basically used when wanting to know who, when, and what are visitors coming to your company or store.

9.     Correlation Analytics: when you need to find out if there is a relationship between two or more variables, and want to know how strong this relationship is, you can use this statistic tools to get your answer.

10.   If your data is collected through time, you need to use Forecasting and Time Series Analysis. Based on what happened in the past, this tool can find out significant statistics from the data characteristics and can predict the future of it.  

11.  Linear Programing: It is also called linear optimization, and it uses a linear mathematical method to identify the perfect and best result. In addition, it provides problem solutions to increase and decrease the profit and cost. If you want to get the best answer of combinations from basic raw materials, this is the right tool to use.

12.  Neural network analysis: It is a network of the computer programs that knows how to work with a large amount of information and process the patterns in a similar way to what human brain does. Therefore, it is the best technique in working with big data.

Those twelve tools were just some of what a manager should know and understand exactly how it is used in order to deal with any changes with variables. Extra tools might differ in their benefits, but eventually, all are very important to accomplish the objective of the company.

https://www.forbes.com/sites/bernardmarr/2016/02/04/the-18-best-analytics-tools-every-business-manager-should-know/2/#20ad80912e84

Why Digging Through Big Data is Like Cleaning Your Closet!!

Whenever looking in my closet or cleaning it, I always find something new I had forgot about or didn’t even know I had. Diving into data is similarly the same thing. You get to find information and insight out of it that gives you beneficial findings. Cleaning up your closet and going through data are both overwhelming processes. To have the chance to find valuable information in your data, you need to pass a lot of action in order to find remarkable findings, and that applies on both cases, data and closet mining.

            First, you need to translate the business needs into the key performance indicators (KPI’S), and after that, determine the data sources. Then, you connect and build connecters. This will help in getting data in the right place to get to use it. After that, you need to mark which data gets to stay to be stored, and which one gets abandon. In this same step, you will have to choose a method to start the storage of data and visualization. To make it simpler, just think of your closet, you need to assort all pants together, winter clothes with winter appurtenances, and so on. After sorting the data into its final shape, you will use filters and clusters to segment your data to visualize it. This is just like being creative with your clothes from your closet and making different outfits your closet offers you.

https://www.tibco.com/blog/2013/07/11/how-setting-up-a-search-analytics-program-is-like-cleaning-your-closet/

How did business intelligence shift to artificial intelligence?

Nowadays, anyone can use tools in the field of business intelligence, data or analytics. The process had gotten much easier for an ordinary person to transform any piece of data they have into beneficial information that can be used in making business decisions. With just simple steps, and no matter how well you know about data or analytics, you can take better decisions by diverting any amount of data you collected. However, due to the massive increase change in the data flood and continuingly growing, it is becoming a major problem for business tools to be able to give the perfect answer or insight on that data. Anne Moxie, a senior analyst at Nucleus Research, once said: “By 2018, most business users will have access to self-service analytical tools, but the fact remains that there’s too much data for the average business user to know where to start.”

            Even though these tools (self-service tools) are now available to be used, still, the majority of business companies lack the most important skill, the analytical skill, to recognize the data that holds the most serious and remarkable information they could lay hands on. In a recent article in Data Knowledge, GoodData CEO Roman Stanek once said that predictive analytics, radical advances in computer power, machine learning and artificial intelligence made up a new generation of beneficial tools in analytics. If people get to use these tools in the right proper way, they might have systems that generates big data instantly from complicated data sets into effective business actions. This, in fact, is not too fictitious. Recently, machines have got the ability to extract information from complex data better the humans. For a business to go forward, they must invest in next generation systems that is mainly focused on strategic issues.  

https://www.gooddata.com/blog/artificial-intelligence-is-the-future-of-business-intelligence