David Menninger's Analyst Perspectives

Big Data for Business: A Requirement for Today’s Business Analytics

Posted by David Menninger on May 13, 2019 6:00:00 AM

Organizations now must store, process and use data of significantly greater volume and variety than in the past. These factors plus the velocity of data today — the unrelentingly rapid rate at which it is generated, both in enterprise systems and on the internet — add to the challenge of getting the data into a form that can be used for business tasks.

To better understand these challenges we recently launched our Big Data for Business benchmark research, which is designed to clarify the big data value chain — data sources, integration and governance of those data sources, analysis of the data and deployment into business processes. The research relies on the participation of organizations using big data and will provide quantitative assessments of the market and deployment guidance drawn from successful big data deployments.

Many organizations struggle to collect, access and process big data using conventional on-premises technologies. Often, this is a losing battle. Without some efficient way to process big data, organizations risk delays and frustration, both of which can reduce the value of VentanaResearch_Big_Data_for_Business_Benchmark_Logocritical information and cause users to lose confidence in it.

One of the most striking new opportunities big data presents for business is to be able to apply analytics to derive previously unavailable insights that can help address many data-dependent management and operational challenges — preventing fraud, for example, or ensuring security or integrating social media comments into customer data stores. But many potential users also aren’t clear how to analyze big data or how best to use it for business advantage. Should organizations invest further into visualization or data discovery tools? Should they instead delve more deeply into artificial intelligence and machine learning? Or do they have the opportunity to go beyond analytics and explore new ways to integrate big data into their operational systems?

Big data thus is a two-sided coin. It creates promising new opportunities to use information to innovate and to improve business functioning. But to take advantage of the opportunities, organizations need efficient processes and effective technology that will make information drawn from big data available to all who need it. Deciding how to approach big data management requires solid information about data and information management tools appropriate for today and also tomorrow — information from objective, methodical in-depth research that presents facts and not the opinions of a few.

This new research will examine four key categories of big-data tools and processes: visual discovery, which enables users to analyze large heterogeneous data sets; artificial intelligence and machine learning, which facilitate identification, classification and deriving predictions from large data sets; real-time and streaming analytics, which provide fast analysis of operational big data in a production environment; and big data management technologies ranging from relational database management systems to Hadoop and NoSQL.  

We also will examine the types of data organizations are collecting, how that big data is being managed and the range of analytic techniques and tools that organizations have applied or are investigating. Through application of the Ventana Research Performance Index we will determine the maturity of organizations’ use of big data by size and industry; the research will provide insight as well into buyer requirements for big data technology and how well the market currently satisfies them. In designing this research, one major concern will be to provide prospects with a better understanding of their organization’s needs and thus improve their ability to formulate a successful internal business case.

Selecting the right approach to big data is difficult when prospective buyers lack knowledge of best practices and functional requirements for their industries and lines of business; deficiencies in their software and data environments further complicate the ability to choose wisely. Indeed, the definition of big data is in the minds of many vague. This research will clarify it. It will explore what big data means to key players within organizations, identify types of big data other than that formatted for relational databases, and evaluate processing capabilities and techniques to handle the proliferation and variety of big data.

This research will examine the use of big data in the real world to discover how organizations effectively derive value from it. It will assess how companies are integrating their analytic approaches with each other and investigate use cases across industries and lines of business in search of best practices and insight into time-to-value.

Management and managers need advice on how to select the approaches best suited for their information architectures. They also need more reliable information than is currently available about integrating historical and predictive analytics into systems and processes to make better use of existing investments and to plan new ones to support making better decisions faster and more consistently.

Click here to participate in this research, and here to learn more about Ventana Research’s methodology and large body of business research. Ventana Research also has conducted research in related areas including Data Preparation, Machine Learning, Data and Analytics in the Cloud, Next-Generation Predictive Analytics and Big Data Analytics and Integration.

David Menninger
SVP & Research Director

Topics: Analytics, Business Intelligence, Data Governance, Data Preparation, Information Management, Internet of Things, Data, Digital Technology, blockchain, data lakes, AI and Machine Learning

David Menninger

Written by David Menninger

David is responsible for the overall research direction of data, information and analytics technologies at Ventana Research covering major areas including Analytics, Big Data, Business Intelligence and Information Management along with the additional specific research categories including Information Applications, IT Performance Management, Location Intelligence, Operational Intelligence and IoT, and Data Science. David is also responsible for examining the role of cloud computing, collaboration and mobile technologies as they affect these areas. David brings to Ventana Research over twenty-five years of experience, through which he has marketed and brought to market some of the leading edge technologies for helping organizations analyze data to support a range of action-taking and decision-making processes. Prior to joining Ventana Research, David was the Head of Business Development & Strategy at Pivotal a division of EMC, VP of Marketing and Product Management at Vertica Systems, VP of Marketing and Product Management at Oracle, Applix, InforSense and IRI Software. David earned his MS in Business from Bentley University and a BS in Economics from University of Pennsylvania.