Menu

Monthly Archives
2022 October

Home / Blog

Data-driven business competitive advantages

Data is now one of the most important corporate resources. It’s helping more and more companies to anticipate future actions through their past activity. Regardless of whether they want to optimize their business processes with data-driven approaches, or expand or improve the interaction with customers based on data, or even introduce a new digital business model. They can diversify their portfolio with a range of different products – from classic to computerized to data-driven – in order to meet increasingly complex customer needs.

Data-driven business competitive advantages

In this context, Data-driven business models are increasingly becoming a decisive factor in competition. More and more companies are asking themselves how they can use data profitably in their business. But one should know that success does not depend on the pure availability of infinite (often unused) amounts of data. The challenge here is to combine structured, partially structured and unstructured data from different contact points with customers such as social media, sensors, mobile devices, sentiment data and call logs. With the right analysis of the data, more targeted marketing campaigns and better customer integrations desired results are achieved.

 

The analysis of data offers many advantages. Here below is a selection of possible application scenarios:

 

  • Analysis of customer behaviour: Insights and actionable information are gained through data analysis such as how the customers interact with your company so you can uncover ways that can better suit your customers’ behaviour patterns and increase your conversion rate.
  • Profiling of customer groups: Trends and patterns can be identified such as which customers looked at which products for how long? This also gives the opportunity to tailor the future collection to the tastes of certain customer groups. The importance of this process cannot be overestimated, especially for small businesses with limited resources.
  • Dynamic pricing: Thanks to analytics, companies can adjust their prices in real-time according to the market demand, consumer behaviour, available inventories and competitive situation as well as to financial targets and delivery conditions.
  • Personalized customer journey: Today’s customers are interacting with companies across multiple channels. Therefore, touchpoints across all those channels must be analysed so that a personalized and precise approach with the individual offers can be offered. AKA, The right product at the right time at the right price.
  • Next Best Action: Automated suggestions for further campaigns, special prices, additional offers, the type of customer approach (e.g. e-mail or telephone) or the intelligent control of online campaigns enable companies to track a dynamic view of their customers and use this information to better anticipate customer needs.

 

The data thinking concept is definitely a key to corporate success, which is based on data. Data-driven businesses open up countless possibilities such as improved customer and market knowledge, better coverage of customer needs, better sales forecasts, more targeted marketing, higher efficiency and much more. The first step is to look inward and work with the data that is already available to develop and advance use cases. The focus must be put on customer needs and the sensible implementation of the use cases so economic success and a positive ROI can be guaranteed.

GDPR with CIAM: THE devil is in the details

The EU General Data Protection Regulation (GDPR) has been in effect since May 25, 2018, It fundamentally changes the requirements for the processing of personal data and gives EU citizens significantly more control over their personal data – no matter where and how it is processed. Organizations around the world must respect certain guidelines on how to deal with the personal data of EU citizens. Anyone who does not fulfils their obligations risks a fine of up to four percent of the annual turnover achieved worldwide or 20 million euros. With that being said, still many the technical requirements of the EU General Data Protection Regulation seem difficult for companies to implement. An overview of what they are and how Customer Identity & Access Management (Customer-IAM or CIAM) paves the way to compliance.

GDPR with CIAM: THE devil is in the details

The articles of the Basic Regulation essentially define how data is collected, stored, accessed, modified, transported, secured and deleted. So, in the age of digital change, companies must find the right balance between compliance with the legal requirements on the one hand and effective customer care on the other.

 

Not only they must give data subjects extended opportunities to have a say in what happens to their personal data. But also, the person responsible requires documented consent from the data subject for the collection, storage and use of the data. Thus, all personal data must be secured using appropriate technical and organisational measures, depending on the probability of occurrence and the severity of the risk. Here below are few main issues that companies are faced with on the road to compliance:

 

  • Insufficient consent of the data subjects: The previously required basic level of consent to data use, including the opt-out procedure, is no longer sufficient under the provisions of the GDPR.
  • Data silos: Personal data is often stored across multiple systems – for example for analysis, order management or CRM. This complicates compliance with GDPR requirements such as data access and portability.
  • Lack of data governance: Data access processes must be enforced app by app via centralized data access policies. These policies are designed to give equal weight to consent, privacy preferences, and business needs.
  • Poor application security: Customer personal data that is fragmented and unsecured at the data layer is vulnerable to data breaches.
  • Limited self-service access: Customers must be able to manage their profiles and preferences themselves – across all channels and devices.

 

A robust Customer Identity & Access Management (Customer IAM or CIAM) solution are able to solve many of these seemingly insurmountable problems in no time.bThese solutions are able to synchronizes and consolidates data silos with tools such as real-time or scheduled bi-directional synchronization, the ability to map data schemas, support for multiple connection methods/protocols, and built-in redundancy, failover and load balancing.

 

CIAM solutions also facilitates the collection of consent across multiple channels and allows searching for specific attributes. Along with enabling mandatory enforcement of consent collection based on geographic, business, industry or other policies, they also offer the customer the opportunity to revoke their consent at any time. CIAM solutions give customers the ability to view, edit, and assert their preferences across channels and devices through pre-built user interfaces and APIs.

Most of the time these solutions include numerous centralized data-level security features, including data encryption in every state (at rest, in motion, and in use), access to recording restrictions, tamper-proof logging, active and passive alerts, integration with third-party monitoring tools, and more more.

 

In this way, a suitable CIAM solution helps to put many technical requirements of the GDPR into practice. And it even goes beyond the requirements of the basic regulation to create safe, convenient and personalized customer experiences – the basis for trust and loyalty.

 

Sources:

Règles pour les entreprises et les organisations

 

What is data loss prevention and why it’s a must?

Data leakage prevention is an indispensable part of modern data protection and IT security strategies. Every organization has sensitive data. As DLP is considered as of the core building blocks of any IT security strategy. In order to ensure reliable protection of critical data, companies must carefully analyze and classify assets and control access to regulated information based on policies. The loss of business-critical data can easily wipe out a hard-earned competitive advantage & business reputation. The goal of Data Loss Prevention is to systematically prevent misuse or loss.

 

 

Many DLP projects fail because the project team start with the wrong expectations and often unrealistic goals. DLP solutions are usually not able to prevent data theft – e.g. through malware or exploits – but only serve to prevent the spread to prevent critical data. Be sure to communicate this distinction clearly to avoid misunderstandings as the project progresses. For a DLP project to be successful, you must first identify your confidential information that is vital to your business, such as your customers’ contact details, your source codes, your contracts and the personal information of each of your employees. Also the discovery phase with inventory and classification must be done at the beginning. This means that it is important to find out which data is actually available in a company and which is sensitive. It is also important to monitor data traffic as early as possible in order to create transparency. With more prevention, less detection is needed. Typically, DLP solutions address three use cases:

 

Endpoint security/endpoint protection: This includes hard drive encryption, optical drive encryption and USB port encryption to prevent data leaks. A successful DLP introduction largely depends on how transparent and seamless the integration on the end devices is.

 

Monitor data transfer: In order to also protect critical data during transmission in the network, you should integrate the DLP solution seamlessly into your groupware, e-mail and instant messaging applications. In this way it’s easier to monitor email and web traffic for sensitive data to prevent data from leaving the company; DLP also helps ensure that this data can only be accessed through encrypted channels and check whether all recipients have the appropriate authorization to access it.

 

Classifying stored data: Determines where files with sensitive content are stored, for example on servers and cloud platforms, to classify the data according to protection requirements and risk potential. It has proven useful to start with three categories: Public, Private and Restricted. In this way, you ensure a quick and easy rollout and always keep an overview.

 

Today, many companies have already started providing security because data leak management can be done at different levels with flexibility. A key success factor of any DLP project is to sensitize employees early on when dealing with critical information. Get all the document creators on board and clearly explain the project goals, if possible, with regular e-learning sessions to refresh the knowledge.

Data Migration: How to overcome challenges during the migration process?

Every IT organization regularly faces the challenge of having to migrate data. Whether from the old memory to a new one, or straight to the cloud. A data migration is more than copying from A to B, especially due to increasing amounts of data and systems that are becoming more complex. Companies must ensure that data migration to a new storage system works smoothly before getting into the entire migration process.

As data continues to grow in importance, data migrations become top priority projects. A failure of migrations can lead the organization into a disastrous situation. For a successful migration, there are many factors to consider. Das these process are complex and require a high level of expert knowledge is required to ensure they go smoothly. Organizations that identify potential problem areas before the migration and plan accordingly ahead of time save time and money on their migration projects. Here below is a list of few but most common data migration problems.

 

Poor data management: Without a holistic overview of your data, it will be challenging to migrate it in a planned, correct and fast manner.In the absence of regular data management, the data lays in an unstructured manner across different systems – and leads to loss of production because important information is either  hard to access or no longer available. Poorly managed data is also expensive because those responsible are constantly expanding memory in an uncoordinated manner. As the migration of grown databases can consume a lot of time and money, it is highly recommended to clean up the data structure in advance to get rid of legacy issues and to optimize storage costs.

 

Manuel migration: Manually migrating an organization’s huge sets of data takes a lot of time and energy & resources. In particular, when data accumulated over decades have to be processed, manual migration is impossible and error-prone. As a solution, company can anticipate automating repetitive parts of migration with advanced migration tools. Not only process automation saves time and money but also increases the quality and data security.

 

Changing the storage system:  The problems with storage migrations increase when an IT administration wants or has to migrate not just to a new array, but to a completely new system – for example when changing providers or when a contract ends. The new system must then be set up in such a way that it behaves exactly like the old one. Otherwise due to the incomplete integrated into the overall IT infrastructure and cause issues.The team responsible for the migration must configure the target systems thoroughly and carefully before the migration.

 

Recognise and avoid copy errors through the verification process::  Project leader responsible for migrating data wants to be sure that it will arrive correctly at its destination. Incorrect coding of directories that are not displayed correctly can cause incorrect copying of the data in the storage systems involved. The log files of the migration, which many responsible persons use for the verification, cannot sufficiently confirm the correct migration, since they ignore possible weaknesses of the copy tools.

Instead, a modern verification tool can scan data, files and folders including metadata at the source and destination and compare them without further downtime. In this way, errors can be found and addressed. The verification of the data after migration using an independent tool with its own algorithm is essential. It is even mandatory in many sectors. The verification tool also documents the data status at the source and destination at the time of the switch, including the rights, so that the complete migration can be proven afterwards.

 

 

Migration are complex projects and require professional analysis, planning and implementation. The companies that have already set up professional data management have an advantage. If you have not yet implemented data management, or if you lack manpower, tools, know-how and expertise, it can be worth seeking advice from experienced data and migration experts or hiring them for both planning and in implementation. Feel free to talk to our experts about your existing or upcoming projects, we’ll be happy to help!.

Hybrid Cloud Management : Where may companies go wrong in cloud storage strategies.

The advantages of the cloud, including lower capital costs, a high level of scalability and agility, business efficiencies or competitive advantages are quite compelling. Not so long ago, it was even predicted that companies would move their entire IT infrastructure to the cloud and leave nothing on-premises. As expected, that never happened. Instead, many companies have opted for a hybrid approach, a combination that brings together both cloud and on-premises. It’s noticed that often the management of hybrid cloud infrastructures gets challenging for organizations, whether its when it comes to compliance with strict regulatory requirements and legal provisions or the issues related to IT security, the move to cloud becomes a difficult choice to make. Known challenges of hybrid cloud management that companies face are listed below.

 

It seems that while many companies have made a long-term decision that “the cloud” is the future, they have since been disappointed by IT manufacturers and suppliers regarding the migration process. Many technology vendors have not made a conscious move toward cloud, meaning their older solutions are not cloud-ready and their newer ones are often cloud-only. This makes the transition very difficult for the companies as it involves a sudden cut in the operating, utilization and cost model.

 

Retrieving data from the cloud is expensive thus cloud storage becomes more expensive than companies initially assume when implementing it. Organizations must first understand what they expect from the data stored in the cloud. If they want to enable granular recovery, analysis and management of this data, then there are more aspects to consider than just moving data in bulk from on-premise storage. It’s all about the ‘’data’’, so cloud data management is key – regardless of the platform.

 

Cloud storage may lead to a lack of transparency regarding hardware and operations if hardware visibility isignored. There has to be some kind of gateway to the cloud. This needs to be an intelligent device that owns and understands the metadata of the content residing in the cloud. If this solution is not robust and intelligent, the company will be blind to the content. As for the hardware used in the cloud, usually the provider will takescare of that. Most major cloud storage solution providers have robust and scalable solutions that can be trusted. Also inadequate security processes can lead a well-designed cloud initiative into a disaster. Often the cloud providers also operate an integral risk management system so that it can measure and derive risks for customers.

 

If data is growing at very high levels, most likely the cloud storage is a sustainable model. The simple economies of scale mean that the cloud is always cost-effective when used properly. A mix of on-premises and public cloud enables a very scalable and cost-effective approach to large-scale storage. Thus, whenorganizations have these controls in place, managing a hybrid cloud is easy.

The future lies in using a cloud data management platform that is independent of the end storage environment. When organizations have an in-place solution for holding the metadata, the final location of the data is almost irrelevant as long as it meets security and reliability requirements.

 

The increasing complexity of enterprise networks with their heterogeneous mix of cloud and on-premises technologies & security systems are considered one of the main hurdles for companies. Xorlogics offers companies a holistic solution for their cloud implementation and aids them to move forward with their public and hybrid cloud strategies at different speeds. Our motto is to help companies to meet all business requirements and to keep their company competitive over the long term. One should not underestimate the importance of an experienced team and proven solutions for teh right cloud adoption, integration & migtation.

Cheap Tents On Trucks Bird Watching Wildlife Photography Outdoor Hunting Camouflage 2 to 3 Person Hide Pop UP Tent Pop Up Play Dinosaur Tent for Kids Realistic Design Kids Tent Indoor Games House Toys House For Children