Lack of data confidence leads to AI failures
More than a third of AI and analytics projects in the cloud are failing due to poor quality data according to a new survey.
The study from data specialist Trifacta surveyed 646 data professionals across different industries and titles to examine how organizations are handling the accelerating transition of data to the cloud, the obstacles of data cleaning for analytics and the time constraints they face when preparing data.
How the real-time data gold rush creates steep learning curves for developers [Q&A]
By 2025, industry analyst firm IDC predicts that 30 percent of all data will be real-time. The avalanche of streaming data frameworks, libraries and processing engines has created a massive learning curve for developers.
We spoke with Craig Blitz, product director of cloud native application platform Lightbend to learn more about where we are in these early days of streaming data development, and how Lightbend's newly launched open source framework, Cloudflow, aims to support developers pursuing real-time use cases.
Overcoming information overload with knowledge graphs [Q&A]
Businesses are generating ever larger quantities of data, much of it in unstructured form. Extracting value from this massive amount of information can be difficult, which is why it can sometimes feel as if there is simply too much data.
Augmented intelligence specialist Yewno believes it has the technology to help people research and to understand the world in a more natural manner, inspired by the way humans process information from multiple sensorial channels. We spoke to the company's CEO, Ruggero Gramatica, to find out more.
How synthetic data can unlock and help monetize information [Q&A]
Big data offers major opportunities for many industries. But in areas like finance where personal information is involved using the information raises worries about privacy.
One solution to that is to anonymize the information in some way. To discover more about how this works we spoke to Randy Koch the CEO of ARM Insight, a company pioneering the use of synthetic data and assisting more than 1,000 financial institutions to monetize their data safely.
Is dark data valuable?
A tsunami of dark data is coming -- data that has never been analyzed, tagged, classified, organized, evaluated, used to predict future states, control other processes or has been put up for sale for others to use. So, what do we do with this data? First, we have to understand that exponentially more is coming. We see this in autonomous technology as vehicles generate four thousand gigabytes per day.
Also data is becoming more complex, as most of it is already in in video or other complicated forms. Seemingly free storage is encouraging people to store more and defer deletion.
New cloud integrations help streamline big data use
As users and enterprises demand more added capacity, particularly for their data-driven workloads, they are increasingly moving towards all cloud or hybrid cloud environments.
This needs cloud data orchestration to accelerate and synchronize data across different environments, and as a result users are turning to cloud data analytic services like Amazon's EMR and Google Cloud's Dataproc that reduce hardware spend, eliminate the need to overbuy capacity, and provide business agility.
New solution allows contact centers to collect real-time analytics data
Data is more important for business than ever and that is particularly true of contact centers. Access to accurate data from calls and payment transactions is essential to give them a competitive edge.
Data security and compliance specialist Semafone is launching its new cloud-based Intelligence+ solution that offers real-time data as transactions occur.
Talent shortage holds back data analytics projects
Although organizations are becoming more data driven, projects are being held back by a shortage of skilled staff according to a new study.
The research by data science specialist Alteryx surveyed IT decision makers across the UK and five other countries in Europe, the Middle East and Africa (EMEA) and Asia-Pacific (APAC) and finds 77 percent agree that data is a critical corporate asset for driving the business forward.
Lessons learnt from over a decade of Hadoop
Back in 2006 Apache Hadoop emerged and soon began to revolutionize the nascent world of big Data. It’s one of the key factors that helped shape a new industry and -- with the cloud -- helped drive a raft of new consumer industries and business services.
But the data lakes of Hadoop became a challenge to manage, and many Big Data and analytical projects became more of a quagmire than a sparkling lake of truth. What’s more the number compute engines overpopulated. They were operationally complex and demanded specialized skills to maintain. Those data lakes became very disparate compute engines, sharing the same storage whilst they operated disparate workloads. It became a mess. Managing them with the tools available was no picnic.
New data lake solution improves large scale information management
As organizations collect ever larger quantities of data, managing it and making it accessible becomes more of a challenge.
Dataflow specialist Ascend is addressing this problem with the launch of its Structured Data Lake which allows companies to connect their existing data processing engines, business intelligence tools and more to Ascend’s optimized data management system.
IT departments struggle with data growth and inadequate infrastructure
There is global concern about the business impact and risk from rampant and unrestricted data growth according to a new report.
In addition the study from StorageCraft shows that the IT infrastructures of many organizations are struggling, and often failing, to deliver business continuity in the event of severe data outages.
Automated Business Glossary makes enterprise data more available
Data is a resource all enterprises have, but it's only valuable if it's accessible, searchable and understandable. As the amount of data we accumulate grows getting it into a usable form can be a real challenge.
Metadata automation specialist Octopai is looking to make data more easily accessible with the launch of its Automated Business Glossary. This uses machine learning to synthesize data across enterprises and provide one authoritative source for all business operations.
Poor management of data harms businesses' ability to gain value from it
Less than 40 percent of companies in Europe, the Middle East and Africa (EMEA) are confident they can manage, secure and gain insight from data, and use it responsibly according to new research from Oracle.
The study finds that on average 42 percent of respondents do not have a data management strategy in place. Only 35 percent are highly confident they can manage data to generate meaningful insights, and key departments are still not accepting both accountability and responsibility for data management. In addition data security protocols are often not understood, or followed.
How open source is helping remove data silos in the enterprise [Q&A]
Historically data has been stored in silos in order to deliver a quick solution. But in the longer term silos can slow down decision making, make modifying systems harder, and hinder compliance with regulations.
One of the ways to break down barriers between silos is to allow data to be freely shared between them and open source has a big part to play in this. We spoke to Mandy Chessell, distinguished engineer at IBM Cognitive Applications, and recently elected leader of the Technical Steering Committee of the ODPi, to learn more.
15 percent of IT professionals have more data sources than they can count
Data is essential for modern business, but managing it effectively can be difficult. Big data can be just too big to handle.
A new survey from unified operations specialist Ivanti looks at the challenges IT professionals face when it comes to silos, data and implementation.
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