A solid information integration and governance program must become a natural part of big data projects, supporting automated discovery, profiling and understanding of diverse data sets to provide context and enable employees to make informed decisions. It must be agile to accommodate a wide variety of data and seamlessly integrate with diverse technologies, from data marts to Apache Hadoop systems. And it must automatically discover, protect and monitor sensitive information as part of big data applications.
In today’s highly distributed, multi-platform world, the data needed to solve any particular decision making need is increasingly likely to be found across a wide variety of sources. As a result, traditional manual approaches requiring prior collection, storage and integration of extensive sets of data in the analyst’s preferred exploration environment are becoming less useful. Data virtualization, which offers transparent access to distributed, diverse data sources, offers a valuable alternative approach in these circumstances.
A big data integration platform that is flexible and scalable is needed to keep up with today’s ever-increasing big data volume. Download this infographic to find out how to build a strong foundation with big data integration.
Cloud-based data presents a wealth of potential information for organizations seeking to build and maintain competitive advantage in their industries. However, as discussed in “The truth about information governance and the cloud,” most organizations will be challenged to reconcile their legacy on-premises data with new third-party cloud-based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
Any organization wishing to process big data from newly identified data sources, needs to first determine the characteristics of the data and then define the requirements that need to be met to be able to ingest, profile, clean,transform and integrate this data to ready it for analysis. Having done that, it may well be the case that existing tools may not cater for the data variety, data volume and data velocity that these new data sources bring. If this occurs then clearly new technology will need to be considered to meet the needs of the business going forward.
The data integration tool market was worth approximately $2.8 billion in constant currency at the end of 2015, an increase of 10.5% from the end of 2014. The discipline of data integration comprises the practices, architectural techniques and tools that ingest, transform, combine and provision data across the spectrum of information types in the enterprise and beyond — to meet the data consumption requirements of all applications and business processes.
The biggest changes in the market from 2015 are the increased demand for data virtualization, the growing use of data integration tools to combine "data lakes" with existing integration solutions, and the overall expectation that data integration will become cloud- and on-premises-agnostic.
Apache Hadoop technology is transforming the economics and dynamics of big data initiatives by supporting new processes and architectures that can help cut costs, increase revenue and create competitive advantage. An effective big data integration solution delivers simplicity, speed, scalability, functionality and governance to produce consumable data.
To cut through this misinformation and develop an adoption plan for your Hadoop big data project, you must follow a best practices approach that takes into account emerging technologies, scalability requirements, and current resources and skill levels.
DB2 is a proven database for handling the most demanding transactional workloads. But the trend as of
late is to enable relational databases to handle analytic queries more efficiently by adding an inmemory
column store alongside to aggregate data and provide faster results. IBM's BLU Acceleration
technology does exactly that. While BLU isn't brand new, the ability to spread the column store across
a massively parallel processing (MPP) cluster of up to 1,000 nodes is a new addition to the technology.
That, along with simpler monthly pricing options and integration with dashDB data warehousing in the
cloud, makes DB2 for LUW, a very versatile database.
Directed at cloud architecting concerns, this paper covers streamlining complexity at scale, knowing infrastructure state, and using easily repeatable patterns that bolster security, compliance, and disaster recovery. Get this white paper now.
This spotlight report examines:
• How Manufacturing Operations Management (MOM) or Manufacturing Execution Systems (MES) are key enablers of data management and Digital Transformation. Companies can combine many other opportunities with manufacturing operations in a digital journey.
• Product lifecycle management (PLM) as a high-value discipline to pair with MOM in discrete manufacturing, and the value of digital continuity across engineering, manufacturing operations, and supply chain.
• A robust integration of MOM and PLM technologies and the advent of the Digital Twin (a virtual copy of the product and how it's made) to demonstrate maturity in Smart Manufacturing and the ability to make smart products in smart factories.
The IIoT has opened up a world of opportunity for manufacturers. Take advantage of it.
Despite increased awareness and focus on defending against targeted attacks from both business and security leaders, organizations continue to be breached and suffer the consequences. Many of today’s security investments are simply not aligned to defend against these targeted threat vectors. Advanced threat detection and response should not be a point solution but rather a combination of technologies and core competencies. Detecting and responding to advanced threats should involve tight integration of multiple security technologies, network analysis and visibility (NAV) tools, the ability to automatically generate content such as security rules and signatures, context on attacker history, and overall customization and flexibility to ensure that the solution is fine-tuned for your specific IT environment.
Published By: IBM APAC
Published Date: Aug 25, 2017
The world of business analytics is evolving rapidly, and while there are multiple emerging trends of note, two stand out as particularly impactful. First, there is an expanding and increasingly diverse audience of users that are becoming more analytically active. From mid-level Line-of-Business staff to senior executives on mahogany row, more users in more job functions are taking an increased level of ownership in the insight that fuels their decisions and the underlying data that supports that insight.
The real value of i4.0 comes from the integration of automation, data, analytics, manufacturing and products in a way that unlocks new business and operating models. Are you ready for the next industrial revolution?
Read this report to find out:
• why deep pockets alone won’t ensure i4.0 success
• how to scale up projects and capabilities to drive enterprise-level value
• what capabilities, controls and culture are required to support i4.0 success
• how to unlock value by integrating smart processes and smart products
• how to bring suppliers and value chain players into the i4.0 environment.
Leading banks have been talking about integrating risk and finance operations with the aim of securing a single, consistent and multidimensional view of their businesses for years. But with a few exceptions, relatively little progress has been made.
Read this insight to find out:
• why the time to act on risk and finance integration is now
• what value integrated risk and finance operations can deliver
• what shape a new integrated capability might take
• how to prepare the ground for effective transition
• key dangers to address to achieve successful transformation.
Download the insight now
The traditional IT organisation is struggling to meet the insatiable demand for new digital capabilities from business stakeholders. It’s time for a new IT operating model – ¬but what will it look like?
Read this insight to find out:
• what three new roles the future IT operating model must encompass
• what new skills and positions will be required in the IT function
• which integration needs the future IT function must address
• what the priorities should be in terms of orchestrating the IT ecosystem.
Read this insight now
Communication solutions are reaching an ideal balance of sophistication and ease-of-use. But are you making the most of these technologies by integrating them into your daily workflows to make innovation and collaboration part of every interaction?
How are you collaborating with the amazing communication technology now available? Chances are your organization is doing collaboration ... all wrong. Let's look at 5 common collaboration fails tripping up companies today.