Behavioral analytics and why it's important to threat detection and response [Q&A]


Traditional rule-based security techniques centered on malware signatures and perimeter protection are increasingly unable to cope with the latest, more sophisticated threats.
Taking a more behavior-based approach to spotting unusual or risky activity offers a solution, but what is required to make it work? We spoke to Sanjay Raja, VP of product marketing and solutions at cybersecurity specialist Gurucul, to find out.
The rise of the analytics engineer


The rise of the analytics engineer pays homage to the evolving complexity of modern data analytics. The role encompasses many fields, and is closer to software engineering than traditional analytics, as it involves writing programing scripts and maintaining data as a set of software-producing artifacts.
It’s within the context of a rising awareness of the data ecosystem that the demand gap between data scientists and analytics engineers is closing. Once heralded as the 'sexiest job of the 21st Century', analytics engineers are set to soon steal this accolade away from their antecedents.
Organizations vulnerable to emerging threats as they struggle with malware analysis


Almost every organization is struggling with malware analysis according to a new report from infrastructure protection company OPSWAT.
The study finds 94 percent of organizations are finding it challenging to recruit, train, and retain malware analysis staff. In addition 93 percent of organizations are challenged by malware analysis tools that lack automation, integration, and accuracy. This leads to over 20 percent of organizations reporting they are unable to investigate and resolve a majority of their malicious files or alerts.
The future of business analytics will look similar to your favorite app


Imagine a world where more than 300 million people use analytics to make data-driven decisions every day, decisions that require digging through databases, combining multiple sources of data, and even the most advanced analytics techniques. Don’t believe it? This world already exists. Most of us just don’t know it.
Spotify currently has 381 million users listening to music and podcasts. Netflix just reported that it has 221 million subscribers streaming movies and shows across the globe. It’s estimated that 100 million people use an Apple Watch, and many more millions use other wearable fitness devices as well. The list goes on. These companies help millions of people discover new artists, find a show to watch, and even live healthier lives. Their users are everyday consumers, not business analysts or data scientists, and yet they’re somehow making decisions using insights based on the largest and most complex of data sources. If you want to see the future of analytics in business, look to the leading consumer apps.
3 secrets to boost user adoption


Analytics is a transformative tool for business. According to Hanover Research, four of every five users consider analytics integral to their business role. Three of four data pros claim they’d adopt a new analytics platform embedded into their existing workstream. As employees are relied upon to make more data-informed decisions more often, it’s imperative that they fully understand the insights that analytics provide. Equally critical is that those analytics contextualize data and bolster data literacy among everyone along the chain of command.
The desire for user-friendly data analytics in easily accessible formats is strong, and supplying them makes data analysis less overwhelming, more precise and, ultimately, profitable. To accomplish this, implement three key priorities to ensure the chosen analytics suit their purpose, are fully adopted and are continuously utilized.
Quantum is the future say enterprise execs


Those who fail to adopt quantum computing are in danger of falling behind, according to 75 percent of enterprise executives in a new survey.
The study, carried out by Wakefield Research for Zapata Computing, surveyed 300 leaders at large enterprises and finds that 69 percent either have adopted or plan to adopt quantum computing the near future.
When is it time to adopt analytics?


Companies considering expansion strategize over multiple areas of their organization to see where, how, how much and at what cost this growth must occur. They’re looking at business ability, capacity, potential as well as longevity.
The organization will rely upon compiled proprietary data as it sorts through its business intelligence. What must also gain scrutiny during this time are the analytics tools being used to accomplish the assessment, and how long those instruments will be able to deliver at the scale that the business will demand.
Why real-time analysis is key to making better use of data [Q&A]


Businesses of all types generate ever larger quantities of data, but while this should be an invaluable resource to drive decision making the sheer volume can create difficulties.
Analyzing data in real time is the ideal but it can be surprisingly hard to achieve. We talked to Ariel Assaraf, CEO of data streaming specialist Coralogix, to find out how enterprises can face the challenges posed by real-time analysis.
Embedded analytics is the future of analytics


Digital transformations have taken over corporate America. Over the last few years, businesses of all sizes have discovered much of their success now relies upon the ability to quickly interpret incredible amounts of data. While the business intelligence space grows exponentially, traditional BI tools still struggle to keep pace with the need for quick, decisive interpretation of this information surge.
Embedded analytics has inserted itself into this dilemma as the nimble, robust solution.
COVID-19 boosts digital transformation and continuous intelligence


There aren't many good things to come out of the COVID-19 pandemic, but a new study from Sumo Logic shows that it has accelerated digital transformation and piqued interest in adopting continuous intelligence.
Continuous intelligence (CI) allows real-time analytics to be integrated into business operations. Sumo's study shows that 74 percent of cloud-mature companies recognize the value of providing access to real-time data in this way, while 58 percent of organizations going through cloud transformation agree.
You don't need tableau: How to integrate analytics into the apps you already have


In recent years, organizations have invested billions of dollars outfitting employees with traditional business intelligence (BI) tools. Yet, the vast majority of employees still have not bought into the trend. That's not because company BI and industry data underpinning those platforms aren't robust. It's because the analytics necessary to allow companies' knowledge workers to recognize shifting metrics, make timely business decisions and remain at the forefront at interpreting industry trends must be more intuitive and customizable than traditional platforms achieve.
Insight from nearly 2,000 knowledge workers compiled earlier this year by Hanover Research shows that virtually all of them spend time looking for information their BI platform doesn't provide. Three out of four said they would likely adopt a new analytics solution if it was embedded within an application. This reveals a disconnect between their desire to use data analytics in decision-making and the ability to draw upon intelligence tools at their disposal. To avoid such meandering on a one-size-fits-all pathway, instead, incorporate embedded analytics and seek deliberate functionality to achieve maximum value from BI.
IT leaders struggle to support unstructured data in the cloud


The majority of organizations are managing more than 1PB of data and spending more than 30 percent of their IT budgets on data storage and protection, according to a new report into unstructured data from data management company Komprise.
Based on responses from 300 IT storage decision makers at companies in the US and UK, it finds 65.5 percent of organizations spend more than 30 percent of their IT budgets on data storage and management.
Facing the business challenge of open data [Q&A]


We're all familiar with the term 'big data' but not perhaps with 'open data'. Open data is information that can be freely reused and distributed, it's often linked with mixing datasets too.
But what challenges does dealing with open data present for enterprises? We spoke to Mo Ladha, product manager at content services platform Hyland, to find out.
Majority of enterprises lack mature data strategy


A new study reveals that 70 percent of enterprises lack a mature data strategy. The study from cloud migration and managed services company 2nd Watch finds only 26 percent have any data strategy at all.
Most organizations recognize the importance of comprehensive data management though with 60 percent of respondents claiming to have an enterprise-wide data catalog.
Over two-thirds of enterprises fail to exploit valuable data


Despite the fact that data is a key resource for business decision making, a new study reveals that many businesses are leaving it untapped.
The research by Dimensional Research for data integration company Fivetran shows that 44 percent of respondents say that key data is not yet usable for decision making and 68 percent say additional business insights could be extracted from existing data if they only had more time.
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