Businesses are always looking for ways to grow and to streamline their operations. These two goals can come into conflict because as organizations become larger it becomes more complicated to be agile and efficient. To help them understand and modify their processes, businesses can derive insights from analytics applied to their data. Today that data is available not only in the enterprise and cloud computing environments but also from the Internet. To collect, process and analyze it all is a challenge, one that an increasing number of organizations are meeting through the use of big data technologies. The resulting insights can help them make strategic business decisions such as where to focus efforts and how to engage with customers. At Ventana Research we have been working hard to understand the advancing technology that supports big data and its value through information optimization and bring clarity to the industry through our research and analysis of trends and products. There are many opinions about big data and fixation on the attributes of it through the V’s (volume, variety and velocity) and how to use it, often biased toward one technology or vendor; our research and analysis of the entire market cuts through the noise to provide not just facts but insights on best practices and methods to apply this technology to business problems.

There’s no doubt that big data can help organizations turn their information assets into insights that are critical for achieving growth and interacting more successfully with customers. It can help them access and integrate information for business use in ways that were not possible before. Among these new methods are simpler ways to access and consume information, including search based on natural language and cognitive computing, which is bringing forward advanced science to the processing of information. Big data also enables more effective visualization to support discovery and exploratory analytics. Machine data can be used to gain insights into the workings of technology that directly impacts the operations of the organization. We assert that big data drives operational efficiency through effective processing technology that expands the use of information though analytics and these innovative computing methods. The importance of these advances is shown in our recent benchmark research on information optimization, in which two-thirds (67%) of organizations said that improving operational efficiency is the leading reason to change how they make information available.

In 2013, large steps forward were made in big data technology. We saw the beginning of convergence among technological approaches as Hadoop, in-memory processing and data appliances intersect with specialized and traditional database systems. Users are learning how to gain value through insights from these technology investments. While we saw advances in visualization as shown in our predictive analytics research, using most of these tools requires advanced skills to ensure that the data is interpreted properly for facilitating actions, let alone decisions. Many organizations lack these skills in-house, our research shows.

Thus one challenge for 2014 is to acquire the competencies needed to get the best possible information from big data. Another is to improve processes for information optimization so that data, even about real-time events, can flow to business users and reduce the time it takes for them to use it effectively. New platforms and services can help make more types of information easier to understand and interact with. This is complemented by collaboration tools that can operate across mobile devices and get more information to more people wherever they are. We note also that unstructured data such as documents, images and text now is part of the information requirements for more than half of organizations that could use big data technology.

All of these tools and efforts towards information optimization can be useful as organizations try to improve the consistency and governance of their business-related information assets in key areas such as product information management and reduce duplication and conflicts in information about customers and employees along with focus on governance, risk and compliance (GRC). Failing to address these issues can lead to lost revenue, dissatisfied customers and decreased efficiency, all of which impact profitability. Our focus on product information management will continue as it is in high demand: We will release a new Value Index on the topic in 2014 to assess vendors and products and guide potential purchasers. There also have been advances in applications to help businesses manage information; for example, the use of master data management and data governance can help increase accuracy and outcomes from related business processes. In 2014 we will assess the current market for master data management as it impacts both business and IT through new benchmark research and continued coverage of technology developments. Because data no longer resides only in the enterprise, we will continue to track advances in using cloud computing for business applications and accessing and integrating the large amounts of data there. Cloud data is now a major factor in many organizations, and we will reassess the challenges with data in the cloud benchmark research to determine where investments and processes have progressed and where they still need to be improved.

Mainstream use of big data is leading organizations to invest in creating a new stream of information processes that can meet a variety of business needs. We have a whole line of new next-generation analytics research in the specific lines of business; the first are for finance, customer and human capital, and other areas planned for 2014 are in sales and marketing, which are still in the early adoption phase of big data but have generated significant interest about its potential.

Organizations have several options in the types of big data technology they choose. Some are using Hadoop and commercial versions of it from a variety of providers, others are using big data appliances, and still others are using in-memory computing and specialized databases. Our latest research finds that in 2014 more organizations plan to use Hadoop (24%), in-memory tools (23%) and appliances (15%) than will use an RDBMS (10%). This variety of technologies is generating new best practices in big data and how to use the resulting information. Big data is a critical innovative technology now important to 41 percent of organizations. Please consult my colleague Tony Cosentino’s research agenda in business analytics and big data, which outlines new methods to discover and explore big data effectively; he also has new research coming on big data analytics.

It is now possible for organizations to learn and apply best practices in using big data effectively across business and IT. Once that is accomplished users can examine how to make information flow easily into applications and optimize their use, too. At this point, however, many have yet to focus on integration of data and sources to ensure an efficient flow both in the enterprise and throughout cloud computing. This challenge we call big data integration, and we are conducting new research to identity the issues, methods and best practices here. Our research shows that for more than four out of five organizations that have 16 or more sources of data it is important to simplify access and use of it all and integration will help address this challenge. This year we will also have our annual Value Index on vendors and products in data integration and will expand to include the requirements for big data and cloud computing. The availability of technology for data integration is fueling new efforts in what I call integration optimization, which even includes handling of real-time event streams in complex event processing to produce operational intelligence. We have research on this and an upcoming Value Index. Use of this real-time information and analytics is helping organizations respond to issues more quickly than waiting for historical analysis to take place.

We expect significant advances in big data and information optimization in 2014. In this market, however, most organizations lack experience and skilled resources. We warn them not to investigate big data just because “everyone is doing it.” That is not necessarily true, so we recommend first reviewing the processes in your organization in which it can provide value, and then look at the architectural and technological approaches that best fit your needs and available resources.

This post was originally published by Ventana Research. Published with permission.