Creating a Big Data Platform Roadmap

Perficient Data & Analytics

One of the most frequently asked questions by our customers is the roadmap to deploying a Big Data Platform and becoming a truly data-driven enterprise. Just as you can’t build a house without a foundation, you can’t start down a big data path without first establishing groundwork for success. There are several key steps to prepare the organization to realize the benefits of a big data solution with both structured and unstructured data.

The business value of a governed data lake

IBM Big Data Hub

Imagine a searchable data management system that would enable you to review crowdsourced, categorized and classified data. Consider that this system would apply to all types of datastructured and unstructured — and become more robust as more users analyze it

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UCSF leverages blockchain for secure sharing of clinical trial data

Information Management Resources

The blockchain-based file and data structure could be used to reliably safeguard data in a clinical trials network. Blockchain Distributed ledger technology Data security

Cisco Talos discovered 2 critical flaws in the popular OpenCV library

Security Affairs

The CVE-2019-5063 is a heap buffer overflow vulnerability that exists in the data structure persistence functionality of OpenCV 4.1.0. If the string does not match one of the strings in the switch statement, the data is instead copied to a buffer as is.”

Doing Cloud Migration and Data Governance Right the First Time

erwin

So if you’re going to move from your data from on-premise legacy data stores and warehouse systems to the cloud, you should do it right the first time. And as you make this transition, you need to understand what data you have, know where it is located, and govern it along the way.

The Top Six Benefits of Data Modeling – What Is Data Modeling?

erwin

Understanding the benefits of data modeling is more important than ever. Data modeling is the process of creating a data model to communicate data requirements, documenting data structures and entity types. It serves as a visual guide in designing and deploying databases with high-quality data sources as part of application development. In this post: What Is a Data Model? Why Is Data Modeling Important? What Is a Data Model?

Legendary Help: Adapting the Customer Experience Amid the Pandemic

Rocket Software

During times of increased demand, the flexible data structures allow for high-performance data access, storage, and resource management capabilities. The global economy is beginning to restart slowly, with businesses opening and individuals returning to work.

How to Create Great CX Using the Full Potential of MDM

Reltio

Improved customer experience (CX) is a key driver in the digital economy, and having optimal multi-domain Master Data Management (MDM) is a core prerequisite for delivering great CX. Customer privacy and data protection settings and rights.

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Common Problems with Content Migrations

AIIM

Data Quality Issues. Any migration involving unstructured data, that is, individual files, is bound to run into issues migrating certain file formats. Reports: Integrated systems may also be generating reports that rely on data from both/all systems involved. Data Quality Issues.

Why You Need End-to-End Data Lineage

erwin

Not Documenting End-to-End Data Lineage Is Risky Busines – Understanding your data’s origins is key to successful data governance. Not everyone understands what end-to-end data lineage is or why it is important. Data Lineage Tells an Important Origin Story.

Executive Order About Cybersecurity Urging Zero Trust Adoption

Thales Cloud Protection & Licensing

prioritize identification of the unclassified data” [Section 3(c)(iv)]. Within 180 days of the date of this order, agencies shall adopt multi-factor authentication and encryption for data at rest and in transit, to the maximum extent” [Section 3(d)].

Best Digital Forensics Tools & Software for 2021

eSecurity Planet

For everything from minor network infractions to devastating cyberattacks and data privacy troubles , digital forensics software can help clean up the mess and get to the root of what happened. Like TSK and Autopsy, OpenText specializes in disk and data capture tools.

How to Do Data Modeling the Right Way

erwin

Data modeling supports collaboration among business stakeholders – with different job roles and skills – to coordinate with business objectives. Data resides everywhere in a business , on-premise and in private or public clouds. Nine Steps to Data Modeling. Promote data literacy.

Integrating SQL and NoSQL into Data Modeling for Greater Business Value: The Latest Release of erwin Data Modeler

erwin

compliance with the General Data Protection Regulation). For decades, data modeling has been the optimal way to design and deploy new relational databases with high-quality data sources and support application development. The Newest Release of erwin Data Modeler.

New TSX Speculative Attack allows stealing sensitive data from latest Intel CPUs

Security Affairs

The flaw affects the Transactional Synchronization Extensions (TSX) feature in Intel processors, it could be exploited by a local attacker or a malicious code to steal sensitive data from the underlying operating system kernel. In the past months, security researchers devised several speculative -channel RIDL (Rogue In-Flight Data Load), Fallout, Microarchitectural Data Sampling ( MDS attacks ), and ZombieLoad.

How to Develop a Metadata Strategy

AIIM

Every system uses metadata to store and retrieve data. But in too many organizations, every system uses similar but different metadata, with the result that different data structures and approaches make information harder to find and manage, not easier.

Benefits of Enterprise Modeling and Data Intelligence Solutions

erwin

Users discuss how they are putting erwin’s data modeling, enterprise architecture, business process modeling, and data intelligences solutions to work. IT Central Station members using erwin solutions are realizing the benefits of enterprise modeling and data intelligence.

We need to talk about Go

Thales Cloud Protection & Licensing

For example, the core “json” package converts JSON to Go structures yet does nothing to automate this process. If you have a large JSON document to consume, you’ll be writing the corresponding Go structures by hand. Thus to solve the problem above, I can turn to [link] , which automatically generates Go data structures that match a JSON document. The post We need to talk about Go appeared first on Data Security Blog | Thales eSecurity. Data security

Integrating Structured and Unstructured Data; Are we there already?

Everteam

“By 2022, 50% of organizations will include unstructured, semistructured and structured data within the same governance program, up from less than 10% today.” Gartner Market Guide for File Analytics. How many companies have separate solutions to manage structured (database, transactional data) and unstructured data (documents, text, videos, images, email, social media, etc.)? Can we look at both types of data in a single governance program?

Six-Library Vulnerability in NGA

ForAllSecure

The US government has published a software library called six-library designed to parse and manipulate satellite imagery and data for both internal and public use. In this case the function called before readTre has the user input stream data structure on the stack.

The State of Blockchain Applications in Cybersecurity

eSecurity Planet

For these industries and more, data storage, identity management, and smart contracts are applications where blockchains could shine. In a few words, blockchains are advanced databases that timestamp and store clusters of data in immutable virtual blocks linked chronologically.

Six-Library Vulnerability in NGA

ForAllSecure

The US government has published a software library called six-library designed to parse and manipulate satellite imagery and data for both internal and public use. In this case the function called before readTre has the user input stream data structure on the stack.

Speculation Attack Against Intel's SGX

Schneier on Security

At a high level, SGX is a new feature in modern Intel CPUs which allows computers to protect users' data even if the entire system falls under the attacker's control. Attempts to read SGX data from outside an enclave receive special handling by the processor: reads always return a specific value (-1), and writes are ignored completely. Another speculative-execution attack against Intel's SGX.

Poulight Stealer, a new Comprehensive Stealer from Russia

Security Affairs

The last instruction seen in Figure 8 is “ CBoard.Start ”, which works in the following way: Figure 12: Routine to steal the clipboard data. Researchers from Cybaze-Yoroi ZLab monitored the evolution and the diffusion of an infostealer dubbed Poulight that most likely has a Russian origin.

Seamlessly discover and extract metadata from your ERP and CRM systems

Collibra

Your organization has invested heavily in these systems, and they continuously generate valuable operational and transactional data. This data is essential to power analytics and support critical business decisions. Data Catalog

Hackers are again attacking Portuguese banking organizations via Android Trojan-Banker

Security Affairs

This service also defines the data structure used and which stores information about the victim later sent to C2, as well as additional validations on the mobile device. The data is exfiltered and sent to C2 via an HTTP – POST request.

Top 10 Data Governance Predictions for 2019

erwin

This past year witnessed a data governance awakening – or as the Wall Street Journal called it, a “global data governance reckoning.” There was tremendous data drama and resulting trauma – from Facebook to Equifax and from Yahoo to Marriott. And then, the European Union’s General Data Protection Regulation (GDPR) took effect , with many organizations scrambling to become compliant. So what’s on the horizon for data governance in the year ahead?

Active metadata graphs and machine learning for Data Intelligence

Collibra

Implementing the right metadata management solution can positively impact an organization’s data strategy to maximize data use and reuse. systems and data sources. data sets. data products. Data stewards link physical data assets (e.g.

Part 1: OMG! Not another digital transformation article! Is it about understanding the business drivers?

ARMA International

Some technology trends such as real-time data analytics are on-going, while others are more recent, such as blockchain. Information and data are synonyms but have different definitions. Therefore, in this article the terms “information,” “data,” and “content” are synonymous.

Government Open Data Success Via Information Sharing, Enterprise Architecture and Data Assets

Interactive Information Management

But that's what's happening all over, isn't it, driven by consumer demand on their iPhones - mashing and manipulating information that's managed to leak through the risk-adverse, highly-regulated mantle of the government's secure data cocoon, and instantly sharing it for further rendering, visualization or actual, productive use. enterprise architecture open data open government

Centralized vs. blockchain: A head-to-head comparison of storage requirements

CGI

Indeed, blockchain’s distributed data structure results in a significantly higher storage demand compared to traditional centralized databases. However, central systems often suffer from a lack of trust, resulting in “hidden” data silos and often additional labor costs. However, as all the parties have a stake in accurate data, each producer also keeps its own production records. Centralized data governance.

Data governance use cases – 3 ways to implement

Collibra

Establishing data as a strategic asset is not easy and it depends on a lot of collaboration across an organization. However, once you have a system of record in place for your data, your organization can implement many valuable data governance use cases more easily. .

Part 2: OMG! Not another digital transformation article! Is it about the evolution from RIM to Content Services?

ARMA International

Some technology trends such as real-time data analytics are on-going, while others are more recent, such as blockchain. AI can analyze this vast amount of data from many sensors and combine it with other sources such as weather forecasts and historical data to recommend options for action.

How automated data lineage improves regulatory compliance

Collibra

Today, banks struggle to comply with BCBS-23 due to an inefficient data architecture within their organization. According to a study conducted by Mckinsey , having an inefficient data architecture is the number one challenge banks face when trying to comply with BCBS-23.

Master Data Migration: Moving From Legacy MDM to Innovative MDM

Reltio

Data leaders and architects want to accelerate their company’s digital transformation and enable connected customer experiences with connected data. But, many are held back because outdated master data management tools are slow, rigid and constrained.

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How to Perform a Content Migration - Your Checklist for Success

AIIM

This will definitely impact the timeline required to do the migration, as well as what happens to the source system and the data it contains. Technical Specialists: A migration could require technical support for the movement of data and questions about implementation and data structures. Determine the Value of the Information in the Source System: Does the source system store formal business records such as financial data, personnel files, contracts, etc.?

You May Soon Be Told to “Go Jump in a Lake” for Your ESI: eDiscovery Trends

eDiscovery Daily

A data lake, that is. Leave it to Rob Robinson and his excellent Complex Discovery blog to provide links to several useful articles to help better understand data lakes and the potential they have to impact the business world (which, in turn, impacts the eDiscovery world). A data lake is an architecture for storing high-volume, high-velocity, high-variety, as-is data in a centralized repository for Big Data and real-time analytics.

What is metadata management?

Collibra

Metadata management is a cross-organizational agreement on how to define informational assets for converting data into an enterprise asset. As data volumes and diversity grow, metadata management is even more critical to derive business value from the gigantic amounts of data. .

Cross-Post from Out of the Stacks: How to Convert Your Home Movie Tapes to Digital

The Texas Record

DVDs were considered long-lived at the time they came out, but the writable and rewritable disks are not permanent and are prone to lose data over time – in as little as 10 years! DVD video already uses video compression to reduce its data footprint.

It’s Not Facebook’s Fault: Our Shadow Internet Constitution

John Battelle's Searchblog

Instead of focusing on Facebook, which is structurally borked and hurtling toward Yahoo-like irrelevance, it’s time to focus on that mistake we made, and how we might address it. Bandwidth, responsive design, data storage, processing on demand, generously instrumented APIs; it was all coming together. Google united the Internet, codifying (and sharing) a data structure that everyone could build upon.

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