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Overcoming the top four barriers to actionable data insights
2021-04-08 19:23:56| The Webmail Blog
Overcoming the top four barriers to actionable data insights nellmarie.colman Thu, 04/08/2021 - 12:23 According to IDC, the amount of data created over the next three years will be more than all the data created over the past 30 years. And the world will create three times more data over the next five years than it did in the previous five. As data volume and variety increase and data sources proliferate, new opportunities will arise opportunities to deliver superior customer experiences, drive better business decisions and enable greater agility and resiliency. New technologies and approaches such as the Internet of Things (IoT), cloud native development, AI and machine learning, and the modern data fabric offer a path to this intelligent business vision. Despite these opportunities and new approaches, businesses are struggling to manage data and generate meaningful analysis. Theyre weighed down by issues like dirty data and misaligned data collection and governance policies. These companies risk falling behind competitors, who are using data intelligence to adapt to their customers needs quickly and proactively. To gain actionable insights from your data, youll need to address some common barriers. Lets take a look at each of these, as well as what you can do to overcome them. Barriers and solutions to running a smarter and faster business In a recent study of 1800+ IT leaders, we explored why businesses either fail to move their data analytics projects into production or experience quality and availability issues when they do. The study revealed several key barriers that are common to most businesses: 1. Data discovery challenges Data discovery is difficult when you have unknown data sources, poor data quality, data silos and compliance restrictions. These issues can trace their origin to data used or generated by a specific application stored in a siloed data platform, typically found in an early 2000s web application architecture or in 1990s UNIX applications. Additionally, incomplete views of customers and other business entities, duplicated data and a general lack of understanding around what data is available (for building new applications or updating existing ones) results in less-effective services, insights and customer experiences. Solution: With a holistic view and understanding of your data estate, plus a modern data architecture that makes your data accessible, you can make data discovery and utilization a more natural part of your DevOps processes and culture. DevOps drives speed and quick turnaround. And your data if its known and accessible and in a useful format can be fully incorporated into your DevOps culture, development and deployment processes. 2. Excessive costs When your infrastructure isnt structured for utility and elasticity, your talent is expensive, and youre facing large, ongoing investments with no guaranteed return, costs can grow out of control. Costs also become excessive as you continue to rely on on-premises data solutions for your worst-case scenarios as youre stuck servicing older virtualized applications and data infrastructure. And your on-premises data platforms servicing cloud-based applications may incur higher than needed ingress/egress fees. Solution: By moving data platforms to the right public and private clouds in a multicloud architecture, you get the benefits of multicloud including elasticity, self-service, optimized economics and cloud native services so you can develop modern applications and host a modern data architecture. 3. Complexity Choosing the right mix of technologies, identifying architectural best practices for deployment, and integrating cloud, on-premises and edge these are all complex responsibilities. Yet theyre made even more difficult if your data platform mix isnt optimized. For example, your data may have been forced into a traditional relational data management system, or worse, into unstructured files even though that is not the optimal place for data use and analysis. This makes developing applications using this data more difficult and less effective. IoT dramatically increases the data coming into your business. But it must be analyzed and intelligently separated into data flows that support the business such that your applications get the data they need when they need it. Many organizations either do not leverage the IoT or do so in a manner that overly restricts their data being used from the IoT. While these approaches result in preventing data flooding with its reliability, security and availability issues, they eliminate the benefits of using all of the appropriate data in their business ecosystem. Solution: Dealing with the explosion of data variety, velocity and volume is complex. But by putting this data into the right data platforms in the right clouds configured into a modern data architecture, your data can be more readily used, be more cost effective and set the foundation for modern analytics and superior business insights. 4. Skills gaps Most organizations dont have the skills necessary in-house to optimize their data architecture for modern AI/ML use cases and cloud native applications. To create a modern data fabric, you need specialized education, training and experience not organically available in typical IT teams. This skills gap also contributes to data integration architecture that is scattered and opportunistic preventing applications from getting the right data at the right time and leading to less-than-optimal experiences, results and insights. Solution: Work with a partner whose team has the right skills, career paths and continuous work experience where theyre always busy solving problems and building expertise across many different industries and use cases. This helps ensure that theyre able to attract and retain the best data people. Achieving actionable data insights With a modern data architecture, your data can help drive better business processes, experiences and decisions. And with a fully integrated data environment supported by DataOps and MLOps, your business and IT teams can make intelligent business and IT decisions that will drive the most value to your customers and have the greatest impact on your businesss bottom line. Modern data architecture coupled with AI and machine learning enables your business to get the right data to the right application at the right business moment while delivering a new level of business insights and intelligent applications. To learn more about how organizations are managing and modernizing their data, check out our report, Data modernization: R
Tags: top
data
barriers
insights
Intel updates Xeon scalable processors for faster data centre, 5G applications
2021-04-07 09:42:00| Telecompaper Headlines
(Telecompaper) Intel has launched its new Xeon Scalable processors. Code-named Ice Lake, the third-generation server chips target applications such as data centres and 5G networks...
Tags: data
applications
centre
updates
LYTT Launches Real-Time Well, Reservoir Data Visualization Dashboard
2021-04-06 16:38:03| OGI
LYTTs cloud-based spotLYTT dashboard livestreams dynamic production data to operators workstations anywhere in the world, giving unprecedented visibility.
Tags: data
launches
reservoir
visualization
Hacker Recycles Data on Half a Billion Facebook Users
2021-04-06 13:00:00| TechNewsWorld
A rich cache of data on some 533 million Facebook users was posted to a hacker forum over the weekend and is available to download for practically free. In a statement provided to TechNewsWorld by Facebook, the company said it is confident the posted information is old data that originated from a weakness in its contact importer feature that was discovered and fixed in August 2019.
Payload Data Ground Segment System Engineer
2021-04-06 11:13:24| Space-careers.com Jobs RSS
Position Reference 857 In order to integrate the Ground Segment Operations Centre part of the Space Systems department of this wellknown organization, we are currently looking for a Payload Data Ground Segment System Engineer to work at our clients premises in the city of Rome, Italy. This PDGS expert will have the opportunity to share hisher experience in the field of technical supervision and coordination of Payload Data Ground Segment engineering and AIV activities. Tasks and Activities The scope of work will include Technical responsibilities on SAR or Multispectral Processors, Hyperspectral and Thermal Processors, but also processing Infrastructures, Catalogue and Archive Systems, and coordinating subcontracted CALVAL Facilities subsystems activities. Technical realisation and coordination of Payload Data Ground Segment engineering and AIV activities. Realizing and supervising subsystems design down to component level. Preparation of subsystems technical requirements specifications. Definition and justification of SS architecture, from concept to detailed design phase. Definition and control of SS technical interfaces, internal and external towards space and launch segments. Engineering budgets and SS performance. Skills and Experience The following skills and experience are mandatory Masters degree in Aerospace Engineering or similar academic cursus. Professional experience of at least 3 years in Ground Segment engineering projects for space systems. Proven experience in definition and design of Payload Data SS for EO systems. Strong competences in design and development of EO space systems. Strong competences in the Commissioning activities with regards to calibration and validation of EO systems. Experience in the definition, management and traceability of requirements structure with the support of DOORS or other similar tool. Use of simulation tools for the definition of GS performances, e.g. Stk, MATLAB, IDL, Python. Proven capability to define of GS design throughout the support of model based methods, techniques and tools e.g. SysML, UML, Capella MBSE. Sound knowledge of ground system engineering processes, and ground system and software life cycles. Sound knowledge of relevant ECSS standards. Experience with coordinating partners from different companies in an international project. Results oriented attitude. Planning and organizational skills. Capability to build trust and show inspiring leadership based on strong indirect management skills. Fluency in English, both written and spoken. Italian is an asset. How to Apply Looking to take your career to the next level? Interested applicants should submit their CV and Cover Letter to RHEAs Recruitment team at careersrheagroup.com no later than 17042021. Preference will be given to candidates eligible for an EU or national personal security clearance at the level of CONFIDENTIAL or above. This position is open to protected categories under Italian Law 6899 Rules for the right to work of disabled people. Questa posizione e aperta alle categorie protette L. 6899.
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data
ground
engineer
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