Jeromy  Lowe

Jeromy Lowe

1597951200

IBM AI-Powered Data Management Software Subject to Simple Exploit

A low-privileged process on a vulnerable machine could allow data harvesting and DoS.

The IBM’s next-gen data-management software suffers from a shared-memory vulnerability that researchers said could lead to other threats — as demonstrated by a new proof-of-concept exploit for the bug.

The IBM Db2 is a family of hybrid data-management products containing artificial intelligence, which can be used to analyze and manage both structured and unstructured data within enterprises.

According to researchers at Trustwave, the recently disclosed bug (CVE-2020-4414) arises because the platform’s developers forgot to put explicit memory protections around the shared memory used by the Db2 trace facility. If exploited, it could lead to denial-of-service (DoS) or information disclosure.

#artificial intelligence #data management #db2 #exploit #ibm #poc #proof of concept #security vulnerability #shared memory bug #trace facility

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IBM AI-Powered Data Management Software Subject to Simple Exploit
Siphiwe  Nair

Siphiwe Nair

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Jeromy  Lowe

Jeromy Lowe

1597951200

IBM AI-Powered Data Management Software Subject to Simple Exploit

A low-privileged process on a vulnerable machine could allow data harvesting and DoS.

The IBM’s next-gen data-management software suffers from a shared-memory vulnerability that researchers said could lead to other threats — as demonstrated by a new proof-of-concept exploit for the bug.

The IBM Db2 is a family of hybrid data-management products containing artificial intelligence, which can be used to analyze and manage both structured and unstructured data within enterprises.

According to researchers at Trustwave, the recently disclosed bug (CVE-2020-4414) arises because the platform’s developers forgot to put explicit memory protections around the shared memory used by the Db2 trace facility. If exploited, it could lead to denial-of-service (DoS) or information disclosure.

#artificial intelligence #data management #db2 #exploit #ibm #poc #proof of concept #security vulnerability #shared memory bug #trace facility

Ian  Robinson

Ian Robinson

1624399200

Top 10 Big Data Tools for Data Management and Analytics

Introduction to Big Data

What exactly is Big Data? Big Data is nothing but large and complex data sets, which can be both structured and unstructured. Its concept encompasses the infrastructures, technologies, and Big Data Tools created to manage this large amount of information.

To fulfill the need to achieve high-performance, Big Data Analytics tools play a vital role. Further, various Big Data tools and frameworks are responsible for retrieving meaningful information from a huge set of data.

List of Big Data Tools & Frameworks

The most important as well as popular Big Data Analytics Open Source Tools which are used in 2020 are as follows:

  1. Big Data Framework
  2. Data Storage Tools
  3. Data Visualization Tools
  4. Big Data Processing Tools
  5. Data Preprocessing Tools
  6. Data Wrangling Tools
  7. Big Data Testing Tools
  8. Data Governance Tools
  9. Security Management Tools
  10. Real-Time Data Streaming Tools

#big data engineering #top 10 big data tools for data management and analytics #big data tools for data management and analytics #tools for data management #analytics #top big data tools for data management and analytics

Gerhard  Brink

Gerhard Brink

1620629020

Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.

Introduction

As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).


This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management

Enterprise Data Management: Stick to the Basics

Lots of people have increasing volumes of data and are trying to run data management programs to better sort it. Interestingly, people’s problems are pretty much the same throughout different sectors of any industry, and data management helps them configure solutions.

The fundamentals of enterprise data management (EDM), which one uses to tackle these kinds of initiatives, are the same whether one is in the health sector, a telco travel company, or a government agency, and more! Therefore, the fundamental practices that one needs to follow to manage data are similar from one industry to another.

For example, suppose you’re about to set off and design a program. In this case, it may be your integration platform project or your big warehouse project; however, the principles for designing that program of work is pretty much the same regardless of the actual details of the project.

#big data #bigdata #big data analytics #data management #data modeling #data governance #enterprise data #enterprise data management #edm