Big data analytics used to be the province primarily of large organizations and companies with businesses revolving around data, such as marketing and information services providers. However, with cost factors less of a barrier today -- and the availability of a broader range of big data platforms and software -- the technology is being adopted by a growing number of data-driven companies of all sizes across all industries.
These companies are using big data analytics software to rapidly analyze massive amounts of data in real time, including structured transaction data, unstructured data such as social media posts, log files from mobile applications and machine and sensor data. In turn, the insights derived from these analyses can translate into improved operational efficiency, new revenue opportunities and competitive advantages over business rivals.
Big data analytics software is designed to work with big data platforms, which include Hadoop clusters built around commodity servers and scalable distributed storage, NoSQL database systems and specialized high-performance analytics databases. The tools support predictive modeling and data mining techniques and are capable of scaling as more data is incorporated into analytical models.
Sorting through the many products classified as big data analytics software can make your buying decision even more difficult, as the functionality, features and capabilities of these tools are often similar. Fortunately, we've simplified that process for you in this buyer's guide. Here, we will help you establish your company's specific objectives and map them to the attributes of products and suites from nine of the top commercial and open source big data analytics software vendors. This will aid you in narrowing down your list of candidate vendors to the ones whose products best address your organization's specific big data use cases.
Insight into big data and advanced analytics tools
Learn how companies are adopting big data analytics to solve a variety of data-driven needs and increase their profitability with insights derived from the analytics process.
Big data analytics is a trending practice that many companies are adopting. Before jumping in and buying big data tools, though, organizations should first get to know the landscape. Continue Reading
2Do I need?-
Is big data analytics software a good investment for your organization?
The use cases presented here can help you can determine if big data analytics software could benefit your company's data analytics needs.
Big data analytics tools have a lot to offer and come in many varieties. Get to know some of the ways business users and data scientists can use the software. Continue Reading
By submitting your personal information, you agree that TechTarget and its partners may contact you regarding relevant content, products and special offers.
3How to buy-
Assessing your must-have features for big data analytics software
Here, we examine the specific attributes that can be used to assess how well the various big data analytics software packages available will meet your organization's needs.
4Which should I buy?-
Evaluating big data analytics software from the leading vendors
It's challenging to select a product based solely on functionality, as many tools have similar features. Here, we examine several additional considerations that may factor into your buying decision.
By comparing and contrasting big data analytics software from the leading vendors, you can find the tool that best meets your needs. Continue Reading
5The top big data products-
Big data analytics software from the market leaders
Get overviews of the top big data analytics software products on the market today, with insights into features and how these tools can be implemented.
The Alteryx advanced analytics tool suite comprises three products: the Alteryx Designer desktop tool, Alteryx Server and the Alteryx Analytics Gallery cloud-based application. Continue Reading
The IBM SPSS Modeler and IBM SPSS Statistics predictive analytics tools help users and data analysts build predictive models and manage the analytics process. Continue Reading
KNIME offers open source data analytics, reporting and integration tools, as well as commercial software that can help build more efficient workflows. Continue Reading
Learn about the features and components of the Microsoft R family of predictive analytics tools, which includes Microsoft R Open, Microsoft R Client and Microsoft R Server. Continue Reading
The SAP BusinessObjects Predictive Analytics suite of on-premises and cloud-based tools can be used by data scientists, analytics professionals, as well as less technical teams. Continue Reading
The SAS Enterprise Miner data mining tool helps users develop descriptive and predictive models, including components for predictive modeling and in-database scoring. Continue Reading
The Teradata Aster Analytics platform includes the Aster Database, Aster SNAP Framework, Aster R, SQL-MapReduce framework, SQL-GR and the Aster Analytics Portfolio. Continue Reading