Applications that transform data into meaningful information which helps business make better decisions. The term business intelligence came into use around the 1950s, and it grew out of technology called decision support. Business intelligence system has grown more powerful and comprehensive, mainly due to:
Increased Data Collection: Companies that can easily collect on their customers and on their own internal processes this is due to the rise in things like smartphones wearable devices the internal general computer usage etc.
Greater Storage Capacity: Companies can store data cheaper and in greater quantities than ever before. Companies have access to vast troves of data in the form of smart phone metadata internet usage records social media activity etc.
Business Intelligence platforms can shift through this data to find patterns and trends among purchases or their own internal manufacturing processes by 2018 the business intelligence market is expected to be worth $20.1 Billion.
Main forms of Data:
1. Structured Data
2. Semi structured Data
3. Unstructured Data
Structured Data: Data that resides in a fixed form and it's labeled so this could be name collection boxes on websites or the address fields for shipping information has a header you can put that into excel and you can query it or search it with a computer you can analyze it.
Semi-structured Data: Semi-structured data is a form of structured data that doesn't conform with the formal structure of data models associated with data relational databases.
Unstructured Data: Unstructured data is information that can't be easily read by computers. It's difficult to organize in traditional databases, because it can't be stored in rows and columns. A good rule of thumb is that 80% of all data produced is unstructured.
For example when businesses collect information about Facebook, usage any kind of messages, any kind of comments on walls things like that are all unstructured data.
How do companies store and manage all this data:
It's usually found across:
Marketing automation systems.
Social media platforms.
Data Warehouses: Data warehouses are used to consolidate disparate data in a central location using a process known as extract transform and load (ETL). Warehouses standardize data across systems, which allow it to be queried.
Data Marts are essentially smaller, more focused warehouses. Instead of aggregating data across a company a data mart might store the information of just a single department. Data marts limit the complexity of databases and are cheaper to implement than full warehouses.
How does information get to a central location?
It comprises three basic steps called Extract, Transform and Load (ETL).
Extract: Raw data is extracted from a source program such as CRM or ERP software. This is often step where unstructured data such as notes or author information is tagged with metadata to make it easier to find.
Transform: During this step data is normalized. In order to properly analyze data, it must be in the same format.
Load: Finally, data is transferred into the central warehouse or data mart. This process can occur every week, day, hour or every minute. The more often this is done the more up to date analytic reports will be.
The method of standardizing and centralizing data is known as extract, transform and load (ETL).
What is Handoop?
When people talk about big data and business intelligence Handoop comes up a lot.
Handoop is essentially an infrastructure for storing and processing large sets of data across multiple servers in many ways. Instead of centralizes files, Hadoop uses a cluster system that allows files to be stored on multiple servers. Hadoop can be complex to implement and run, and it is not well suited for ad hoc queries. Hadoop is best suited for companies that produce massive volumes of data such as Facebook or eBay.
Map Reduce is the processing arm of Hadoop. It allows data to be queried and processed on the server where it resides, instead of transporting the data across the network to be analyzed on the computer. This can save huge amounts of network bandwidth and resources.
Hence, business intelligence comprises the strategies and technologies used by enterprises for the data analysis of business information. And it provides historical, current and predictive views of business operations.