Why is this data so important? Because companies can use it to recognize markets, customers and competitors in a better way and therefore impressively hustle towards market and quality of delivery.
However, the data being generated today flows at a very high speed and is very complex as well. Therefore, organizations are discovering and evaluating new technologies and models for analyzing the data and using it to make decisions.
Data Analysis is the process of inspecting, cleaning, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions, and supports decision making. Data analysis can be classified into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA). Descriptive Statistics deals with quantitatively describing the main features of a collection of information. Exploratory Data Analysis focuses on discovering new features in data. Confirmatory Data Analysis deals with confirming or falsifying existing hypotheses. By using big data analytics software you can make way faster decisions with the data that you have.
There are names that pretty much describes the data analysis era in which we live. Apache Hadoop, a nine-year-old open-source data-processing platform first used by Internet giants including Yahoo and Facebook, are the leaders of big data revolution. Cloudera introduced commercial support for enterprises in 2008. MapR and Hortonworks became live in 2009 and 2011, respectively. Among data-management occupants, IBM and Pivotal are those names who have introduced their own kind of unique distribution or Hadoops. Microsoft and Teradata offer matching software and first-line support for Hortonworks platform. There are other big players such as HP and SAP that works with various Hadoop software providers.
SAP has been the biggest winner of the in-memory approach with its Hana platform, but Microsoft and Oracle are now ready to introduce in-memory options for their flagship databases. IBM, Microsoft, Oracle and SAP offer everything from data-integration software and database-management systems (DBMSs) to business intelligence and analytics software, to in-memory, stream-processing, and Hadoop options.
Teradata is focused more closely on data management, and it has close bonds with analytics market leader SAS.
1010data and Amazon Web Services (AWS) have gambled their entire businesses on the cloud model. Amazon has the broadest selection of products of the two, and it’s a clear choice for those running big workloads and storing lots of data. 1010data has a highly accessible database service and supporting information-management, BI, and analytics capabilities that are serving private-cloud style.
Actian, InfiniDB/Calpont, HP Vertica, Infobright, and Kognitio, all of them have cantered their big-data stories around database management systems focused entirely on analytics rather than transaction processing. They have introduced options for high-RAM-to-disk ratios, along with tools to place specific data into memory for ultra-fast analysis.
The new and emerging economy is based on data. This data is being generated, stored, spent and protected at a highly secured level commonly used for currency, gold and other precious metals. Companies keep gathering this data every time they mean business either by talking to customers or dealing with clients and these data analytics software are big help.