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Big Data Trends to Watch in 2017

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Big data continues to be the fastest-growing segment of the information management software market.

New findings released by leading global data, market research, and advisory firm Ovum estimate that the big data market will grow from $1.7bn in 2016 to $9.4bn by 2020, comprising 10% of the overall market for information management tooling.

Ovum’s 2017 Trends to Watch: Big Data report highlights that while the breakout use case for big data in 2017 will be streaming, machine learning will be the factor that disrupts the landscape the most.

Key 2017 trends:
Machine learning will be the biggest disruptor for big data analytics in 2017.

Making data science a team sport will become a top priority.

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IoT use cases will push real-time streaming analytics to the front burner.

The cloud will sharpen Hadoop-Spark “co-opetition.”

Security and data preparation will drive data lake governance.

Under the covers, machine learning is already becoming ubiquitous as it is embedded in many services that consumers take for granted.

Increasingly, machine learning is becoming embedded in enterprise software and tooling for integrating and preparing data.

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Machine learning is placing a stress on enterprises to make data science a team sport; a big area for growth in 2017 will be solutions that spur collaboration, so the models and hypotheses that data scientists develop do not get bottled up on their desktops.

While machine learning continues to grab the headlines, real-time streaming will become the fastest-growing use case.

A perfect storm has transformed real-time streaming from a niche technology to one with broad, cross-industry appeal.

Open source technology has lowered barriers to entry for both technology providers and customers; scalable commodity infrastructure has made the processing of large torrents of real-time data in motion economically and technically feasible.

The explosion in bandwidth and smart-sensor technology has opened up use cases ranging from location-based marketing to health and safety, intrusion detection, and predictive maintenance, appealing to a broad cross section of industries.

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Underscoring and enabling the growth of big data is the growing predominance of cloud computing as the default path to deployment.

Within the next 24 months, Ovum expects that the cloud will pass the halfway mark to dominate new big data deployments.

“Big data has emerged from its infancy to transition from buzzword to urgency for enterprises across all major sectors,” said Tony Baer, Principal Analyst for Information Management. “The growing pains are being abetted by machine learning, which will lower barriers to adoption of big data-enabled analytics and solutions, and the growing dominance of the cloud, which will ease deployment hurdles.”

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Cyber Resilience a Critical Priority for Manufacturing Amid Rapid Digitalization – Report Shows

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As 60% of manufacturers race toward full digitalisation, cyber risk is increasingly manifesting as a business risk, according to a new global report by Kaspersky and VDC Strategy.

This means cybersecurity is not merely a compliance function, it is a cornerstone of production assurance, safeguarding uptime, quality, and operational continuity.

Manufacturers are modernising to deliver safer, more consistent and more cost-effective production and digitalization is moving fast: just 9% of organisations describe themselves as fully digital today, but 60% expect to get there within two years, according to the joint report by Kaspersky and VDC, titled ‘Cyber Resilience, Built for Manufacturing’.

That shift links shop-floor equipment, production lines and site operations to platforms such as Manufacturing execution systems (MES), Supervisory control and data acquisition (SCADA) and historians, turning many plants into cyber-physical systems (CPS), where a digital disruption doesn’t stay digital. It can slow production lines, quarantine work in progress, invalidate traceability records, or halt production outright.

What’s driving manufacturing digitalization?

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Manufacturers are digitising for measurable operational gains, not novelty. Survey respondents identified the primary drivers of their digital transformation strategy as:

  • Improving production output or efficiency (24%)
  • Reducing operational or production expenses (15%)
  • Enabling new strategic opportunities (14%)
  • Improving cyber resilience (13%)

The same connected systems that unlock these gains, including MES, IIoT sensors, automated material handling, remote engineering access, also become the systems that determine whether production can be trusted to keep running.

Cyber risk is now a business risk

Cyber risk has evolved from a mere IT concern to a direct threat to revenue generation, as environments transform into cyber-physical systems. In these integrated settings, digital disruptions like malware no longer just affect data, they can cause unsafe operations, scrapped batches, and halted production on the plant floor. This shift highlights the urgent need to treat cybersecurity as a key part of operational resilience.

According to the report, nearly 60% of manufacturing organisations estimate that cyber incidents cause damages exceeding $1 million per event, with an average disruption of 15.3 hours. The most significant losses often result from production halts, missed delivery commitments, and penalties, rather than just forensic costs.

In this context, downtime links cybersecurity risks to overall business performance. Cyber incidents can reduce Overall Equipment Effectiveness (OEE), strain staffing, and disrupt supply chains. Recovery involves more than system restore, it requires re-establishing confidence in process parameters, quality records, and traceability before resuming operations.

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Mature cybersecurity programs now incorporate OT security into governance, focusing on metrics valued by production leaders such as time to restore, backup confidence, legacy asset coverage, and safe degraded operation. This alignment ensures cybersecurity supports continuous production and resilience, not just IT compliance.

However, challenges remain due to split ownership. While 59% of organisations’ IT departments manage security policies, these often overlook plant realities. Managing many security tools (44%) and OT patching issues (38%) show that cybersecurity must be embedded into daily routines of production, engineering, and quality teams. Only through such integration can cybersecurity effectively enhance operational reliability and defend against evolving threats.

“As manufacturing environments become increasingly interconnected, cybersecurity shifts focus from merely adding protective layers to ensuring the availability, resilience, and integrity of production processes. The goal is to minimise operational impact and speed up recovery, rather than solely preventing intrusions.

“Kaspersky offers a unified ecosystem that integrates IT, OT, and IIoT security, empowering manufacturers to pursue digital transformation securely. This strategy helps maintain operational continuity and reduces long-term cybersecurity costs,” comments Andrey Strelkov, Head of Industrial Cybersecurity Product Line at Kaspersky.

To implement this strategy, manufacturing companies can leverage solutions from the Kaspersky OT Cybersecurity Ecosystem, centered around Kaspersky Industrial CyberSecurity (KICS), a native Extended Detection and Response platform designed for critical infrastructure protection. KICS enables centralised detection and response to complex attacks across the entire industrial network, ensuring comprehensive visibility and security.

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NDPC Probes UNILAG, Lotus Bank, Hackerbella over Alleged Students’ Data Misuse

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Nigeria Data Protection Commission (NDPC) has commenced a forensic investigation into the University of Lagos (UNILAG), Lotus Bank and Hackerbella Ltd over alleged violations of data protection laws involving students’ personal information.

NDPC Probes UNILAG, Lotus Bank, Hackerbella over Alleged Students’ Data Misuse

The investigation follows public complaints alleging that students’ personal data were used to open bank accounts without a lawful basis.

Dr Vincent Olatunji, national commissioner and chief executive officer of the NDPC, directed the investigation team to conduct a comprehensive assessment of the circumstances surrounding the collection, processing, use and disclosure of the affected students’ personal data.

The investigation will also determine the respective roles and responsibilities of UNILAG, Lotus Bank and Hackerbella in the alleged processing of the data.

According to the Commission, the investigation will assess the data protection compliance obligations of the parties under the Nigeria Data Protection Act, 2023 (NDP Act), as well as potential risks posed to the rights and freedoms of the affected data subjects.

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The NDPC said the probe would cover several areas, including Data Protection Impact Assessments (DPIAs), the lawfulness and transparency of credit scoring or profiling activities, and the use of automated decision-making systems.

It will also examine the adequacy of privacy notices, data-sharing arrangements, lawful bases for processing, data minimisation and purpose limitation.

Other areas include data retention policies and the adequacy of technical and organisational measures put in place to safeguard the rights and personal data of affected students.

The Commission reiterated that institutions entrusted with the personal data of students, staff and other members of their communities have a heightened responsibility to ensure that such information is processed lawfully, fairly, transparently and securely.

The NDPC therefore warned educational institutions that are yet to comply with its existing data protection compliance directives to take immediate steps to achieve compliance.

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The Commission said it would continue to exercise its regulatory mandate to protect the privacy rights of Nigerians and ensure that organisations processing personal data comply with the provisions of the Nigeria Data Protection Act, 2023.

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Microsoft to Unveil Next-generation AI Chip in September

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Microsoft is planning to unveil its new Maia 300 AI chip this fall, potentially as soon ​as next month, The Information reported on Monday, citing ‌people with direct knowledge of the plans.

The company introduced its Maia AI chip in November 2023 but has lagged rivals such as Alphabet and ​Amazon in scaling up its in-house chip efforts as ​it seeks to reduce its reliance on Nvidia’s costly ⁠processors.

Google began recognizing revenue from direct sales of its custom ​AI chips, called Tensor Processing Units, in the quarter ended June, ​while Amazon has also seen growing adoption of its processors, including its Trainium chips.

Microsoft has been in talks with chipmaker TSMC to secure manufacturing ​capacity for more than 300,000 units of the chip for ​delivery in 2027, according to the report. It is also looking to significantly ramp up ‌production ⁠and persuade major cloud customers such as Anthropic to adopt the chip.

Microsoft ultimately ​aims to ⁠secure capacity for more than 1 million Maia 300 chips, though component supplies and ongoing capacity ​negotiations with TSMC could constrain its plans, according ​to the ⁠report.

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It unveiled its second-generation Maia 200 in January, built by TSMC using 3-nanometer technology.

Microsoft packed the chip with a significant amount of ⁠SRAM, ​a type of memory that can provide ​speed advantages for AI systems handling large numbers of user requests.

 

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