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Data as a Service: Enterprise search benefits from Artificial Intelligence and Machine Learning

According to IDC, data as a service, voice-controlled apps, and AI-based services are the most important IT trends of the coming years. Data marketing and data analysis are among the most important challenges for companies. IDC expects that the amount of data created in 2023 will reach over 100ZB, one trillion gigabytes), most organizations also need to turn to external data in order to execute a variety of business processes. This translates into more than 90% of large companies generating their revenue from data as a service.

Digital Era ARTIFICIAL INTELLIGENCE MACHINE LEARNING

This is the provision of information and distribution of data for customers. AI-based services and machine learning methods help to interpret data and are therefore becoming increasingly important. In the future, digital services or apps will hardly be able to keep up with the market without the support of artificial intelligence. Artificial intelligence (AI) is a driving force behind digital transformation, encompassing innovations such as machine learning, natural language processing (NLP), data labeling platforms, and predictive analytics. According to IBM 35% of companies report using AI in their business, and an additional 42% of respondents say they are exploring AI.

 

The latest report by Research and Markets also shows that AI is expected to achieve a compound annual growth rate of 52% by 2025, indicating its rapid adoption by global businesses. The global AI spending reached over $55 billion in 2021 (IDC) and the AI market is expected to grow to $1.81 trillion by 2030 (GrandViewResearch). By 2023, 60% of all digitization projects will be supported by artificial intelligence functions and almost half of all apps will be voice controlled. One survey also found that 87% of global organizations believe that AI technologies will give them a competitive edge.

 

The majority of companies are using machine learning processes in marketing & sales, healthcare, banking, manufacturing, and retail sectors. The machine processing of language is becoming increasingly important. Self-learning systems that process complex amounts of data in real time are also gaining importance. AI-based systems are expected to take on more and more tasks and relieve entire departments.

 

The benefits from artificial intelligence and machine learning are numerous:

  • 42% of companies stated that the profitability of their ML and AI initiatives exceeded their expectations, while only 1% said it didn’t meet expectations. (Accenture)
  • By 2025, 50% of companies will have devised AI orchestration platforms to operationalize AI, up from fewer than 10% in 2020.Gartner 
  • Global machine learning as a service (MLaaS) is currently used mostly in healthcare and life sciences, but it is expected to grow in industries including manufacturing, retail, telecom, finance, energy and utilities, education, and the government.
  • 92.1% of companies state they are achieving returns on their data and AI investments. (NewVantage Partners)
  • AI-powered enterprises will be able to respond 50% faster to customers, competitors, regulators, and partners than their peers. (Oracle)
  • AI and machine learning will contribute to the labor productivity increase by up to 37% by 2025.  Industry, Research and Energy (ITRE),
  • 27% of the respondents of the latest McKinsey Global Survey on AI report at least 5% of earnings before interest and taxes attributable to machine learning-based AI.
  • PwC research shows that the global GDP could be up to 14% higher in 2030 (up to $15.7 trillion1 to the global economy) as a result of the ML and AI accelerated development and take-up. (PwC)
  • According to PwC research, 45% of total economic gains by 2030 will be the result of AI-driven product enhancement, stimulating consumer demand.
  • IBM’s new cognitive phishing detection capability uses machine learning to help businesses detect a phishing site up to 250% faster than traditional methods.

Top Tech trends for 2023: What can companies expect in 2023 and position themselves better?

The year 2022 was marked by supply chain disruptions, inflation, debt, labor market gaps, geopolitical uncertainties, fears of recession and increasing ransomware attacks. These developments continue to pose a critical threat to the companies. But it is also important to look into the future at the end of the year to be better prepared for the challenges and opportunities to come & heal covid19 scars.

 

Cloud budgets are being analysed more closely

According to a recent report by Veritas, misunderstanding about cloud security, scalability and storage has led most enterprises spending much more than anticipated. 93% of companies overspend on the cloud, exceeding budgets by an average of 43%. As the amount of data increases every year, the cost of storing it in the cloud also increases. For IT teams, this is becoming increasingly difficult to justify. Exceeding budget is mainly due to the misunderstanding nearly all organizations had that CSPs are responsible for protecting their assets in the clous. Although cloud adoption has enabled most companies to implement advanced business strategies, future CEOs and boards of directors will demand more transparency into the return on investment (ROI) of cloud spending. IT managers are under great pressure to justify their cloud budgets while finding new solutions to reduce data volume as Veritas expect IT spending to be reviewed even more closely in 2023.

The vast majority of enterprises fail to stay within their cloud budgets

Low-code and no-code make compliance difficult

As the demand for hyper-automation and IT modernization is growing at an exponential rate, low-code and no-code applications are contributing significantly to the democratization of application development in companies. In 2023 they will become even more established. The global low-code platform market is forecasted to generate a revenue of $187.0 billion by 2030, increasing from $10.3 billion in 2019, and is expected to reach 31.1% CAGR in the forecast period (2020-2030).

Employees without a technical background (citizen developers) can develop their own applications. Almost 60% of the custom apps are now built outside the IT department. Of those, 30% are built by employees with limited or no technical skills, creating huge compliance issues for businesses. Because citizen developers are less experienced in implementing security and privacy systems. Creating new vulnerabilities that can be exploited by cyber criminals.

 

Edge device vulnerability

Gartner analysts predict that by 2025, around 70% of of the data managed by organizations will be created and processed outside of the data center or cloud vs 10% now. Adoption of edge devices are considered as the solutions that facilitate data processing & generation. But this increasing shift of data processing to the edge complicates the IT architecture and increases the attack surface. Because of the lack of IT specialists, it is often not possible to provide the same level of protection at the network edge as in the data center or the cloud. Nevertheless, to fully protect the enterprise, every single edge device must be secured.

 

IOT & hyper-connectivity

We live in a hyperconnected world where worldwide companies are under huge pressure of shearing and integrating data in a smart way. It’s predicted that there will be more than 43 billion connected devices by 2023 with the goal of generating, collecting, shearing and helping companies to make use to data in the smartest way possible. 5G technologies are also boosting the full potential of IoT & hyper-connectivity. It’s true that IoT devices make our lives easier and more convenient but also comes with huge security issues if not well protected.

As the number of devices explodes during 2023 and beyond, device manufacturers and security experts will have to strengthen their strategies to fight against cyberattacks and minimize the chances of losing valuable data.

Growing threats and risks of Cybercrime

Every day, whether at the personal level or at the corporate level, we are exposed to threats from the cyber space. In most cases, we are not even aware of these threats, or even if we acknowledge them, the right decision isn’t made. The global cyber threat situation has never been as unpredictable as in the covid period, which has set a cybercrime as a record year of ransomware and a breakthrough in crypto-currency-miner attacks. Hackers all over the world took advantage of the COVID-19 situation to launch cyber attacks and it took its toll on businesses, organizations, and individuals alike.

 

Accordingly, companies in all sectors had to contend with serious incidents during this period. The most common causes of critical incidents are the same as last year: targeted attacks (40.7%), malware with critical impact (14%), exploitation of publicly available critical vulnerabilities (13%), and social engineering (5.5%). Targeted attacks in 2021 hit all vertical sectors evaluated in the research except education and mass media, although incidents related to targeted attacks were reported within media organizations. Most human-powered attacks have been identified in government, industrial, IT and financial sectors.

 

The proportion of serious cybersecurity incidents has increased by half in the past year, from 9% in 2020 to 14% in 2021. This is shown by the research conducted by Kaspersky Managed Detection and Response (MDR). Increasingly complex infrastructures, skill shortages, and increasing sophistication of attacks can impact the efficiency of cybersecurity teams and their ability to detect hostile activity before incidents occur. To gain insight into the current threat landscape, Kaspersky analyzed anonymized customer incidents identified through its MDR service in 2021.

Growing threats and risks of Cybercrime

As the ransomware is the fastest growing security threat, known as a moderate or extreme threat by 80% of cybersecurity professionals. Industry experts predicts that, in coming years, this number will continue to increase together with more threats will be added to the known threats. A survey conducted by Veriato Information Security highlighted that Email and web use represent the most common reason of ransomware infection with employees opening malicious email attachments (73%), responding to a phishing email (54%) or visiting a compromised website (28%).
75% of worldwide organizations are touched by ransomware and have experienced up to 5 attacks in the last 12 months alone, 25% experienced 6 or more attacks. The information most at risk from ransomware attacks is financial data (62%)followed by customer information (61%). With such high risk, 59% of organizations are yet not confident at all in their ransomware defence.

 

CryptoTheft, Microsoft Data Breach, Red Cross Data Breach, PressReader’s, the year 2022 has already been marked by major attacks on a global scale based mainly on a security breach. Today, even if this new wave of malware reveals new patterns of attacks, criminals will remain loyal to the most malicious malware: ransomware, financial data, and digital currency crimes. However, the way these threats are used currently will continuously change into sophisticated way.

 

Sources: Truesec: The evolving cyber threat landscape

EU Digital Policy: How DSA and DMA deserves your full attention!

The EU Parliament has given their final approval on the Digital Services Act (#DSA) and the Digital Markets Act (#DMA) to ensure a safer online environment. It marks the beginning of a promising new relationship between online platforms, users, and regulators.

The Digital Services Act is one of the most important digital policy regulations in Europe. In conjunction with the Digital Markets Act, it becomes a kind of basic law for the Internet which established the principles of what should be illegal offline, should also be illegal online.

 

The DSA has the goal to create a comprehensive set of new rules for all digital services, that will strengthens the protection of consumers in the digital world and will create an EU-wide, harmonized legal framework for service providers and platforms – through clear rules for dealing with illegal content and more transparency. No matter if it’s for social media, online marketplaces, and other online platforms that operate in the European Union, DSA will introduces new EU-wide obligations which will have a significant impact on a wide range of digital services that connect consumers to goods, services and content, resulting in a safer digital space and fairer online market creation. The DSA also assigns more responsibility to platforms and is intended to ensure that certain content disappears from the Internet more quickly. Such as, hate speech, terror propaganda or even the sale of counterfeit goods. The law is part of a digital pact.

 

As online services and platforms are an integral part of everyday digital life, the DSA in particular will affect many people directly. They will be better protected online against disinformation, hate speech and counterfeit products. What is illegal offline must also be illegal online and punished accordingly.

 

The DMA, on the contrary, sets out rules defining and prohibiting unfair business practices by large tech giants such as Google and Facebook with stricter rules. DMA is labelled as important gatekeeper between European businesses and consumers. The fact that the Digital Markets Act is also intended to create more freedom of choice between online services is to be welcomed. Fair competitive conditions and easier market access for small and medium-sized companies are essential for innovations. It remains important to specifically promote the growth of European digital companies, to increase investments and to prevent the shortage of skilled workers and the emigration.

What is the Digital Markets Act DMA

 

Sources:

Hyper-Automation: How to achieve tactical and strategic goals by automating business processes

Hyper Automation How to achieve tactical and strategic goals by automating business processes

 

When it comes to digitization processes in companies, hyper-automation is mentioned more and more often. Zion Market Research forecasted Hyperautomation Market  is expected to grow annually at a CAGR of around 23.5 % (2022-2028), it’s was valued at approximately USD 9billion in 2021 and is projected to reach roughly USD 26.5 billion by 2028. It’s one of the big digitization buzzwords, which has come into focus not least because of Gartner’s positioning as one of the top tech trends of 2022.

 

According to the market research company Gartner hyper-automation is the combination of different approaches and technologies in order to get the maximum degree of efficiency out of digital possibilities, by automating automate as many business and IT processes as possible and create end-to-end workflows.

 

Contrary to the pure Robotic Process Automation (RPA), not only individual tasks but also complex processes can also be automated. Hyper-automation cannot be achieved without RPA, artificial intelligence (AI) and machine learning (ML). It all sounds super interesting but how can companies successfully implement this “hyper-automation”?

 

The first step requires a detailed mapping or analysis of the organization and back office processes to fully understand the existing workflows and identify where gaps, latencies and bottlenecks exist. On this basis, a strategy can then be developed to build bridges between the solutions and close efficiency gaps.

 

The next step consist of a wise selection between the different. Given the versatile requirements and complexity of many business processes, a well-orchestrated combination of different technologies is often required. A combination of artificial intelligence and machine learning to workflow tools, business process management (BPM) and robotic process automation (RPA) to low and no-code tools must be foreseen for the use of different application scenarios and problems. By linking previously mentioned technologies, the mapping of complex, cross-departmental and cross-functional workflows can be a piece of cake.

In practice, it’s equal to using process mining tools to better understand business operations & workflows, ML module to verify compliance and decision software to automate maximum tasks.

 

As companies are not only looking towards achieving early ROI but also focusing on optimizing processes, the vendor selection must be prioritized. The providers of different solutions are as diverse as the technologies. The objective must be to ensure that their solutions are easy and rapidly scalable. The cost of integration a technology is comparatively less than that of hiring and training a human. Therefore, organizations need to ensure the selected vendor offers solutions that can easily be integrated and configured in their existing infrastructure. Because every business is different, and there is no such thing as a one-size-fits-all way of doing business.

 

Before you start establishing hyper-automation in your company, you should communicate your automation initiative transparently right from the start and involve employees in the planning and implementation process. They must know how the hyper-automation is going to affect their jobs. Because you may see all the benefits, but your employees might see them differently. They may see a machine replacing them and their work. They must understand that automation increases overall productivity, lessen workload, offers the opportunity for professional growth, and can become a promoter for high-performing and efficient teams.

 

Organizations that want to stay competitive in the long term, must use suitable automation technologies in line with the speed and agility of digital transformation to reach the next business level.

What is sales automation and why it’s mandatory to drive growth?

What is sales automation and why it’s mandatory to drive growth

 

From lead generation through ongoing client support, sales automation covers the digitization and automation of sales activities. B2B companies are slowly but rapidly recognizing the need to put the client at the center of their processes, which forces them to engage themselves more and more in the digital environment. In 2021, nearly 61% of companies that used automation exceeded their revenue targets — demonstrating the potential of sales automation. Yet very few people are aware of the tremendous benefits this provides, especially for sales. Here below are few statements that holds the power to persuade sales managers why they must start with sales automation asap.

 

  • Sales automation is a form of data collector that continuously and automatically gathers the data related to the sales. The sale and purchase experience of a potential client can be improved with each of his recoded activities by using lead scoring to automatically capture and evaluate customer interactions at numerous touchpoints. With the aid of seamless data synchronization in real time, a very detailed profile is immediately generated from this data and can also be mapped directly in the CRM system. Additionally, sales automation aids in determining when and which touchpoints of the customer’s journey are controlled by him.
  • Sales automation gathers a staggering amount of insightful data. As a result, salespeople are better equipped to take into account the preferences and wants of the target market and make smart sales decisions based on reliable data in the CRM system rather than just on intuition. Thus, sales automation becomes the backbone for launching customer-focused sales initiatives and a crucial success element for B2B enterprises’ digital sales.
  • Professional sales automation enables potential clients to be identified at the beginning of their customer journey and then effectively and efficiently followed and developed. As a result, not only the number of qualified leads increases but also the quality of lead grows. Deals are closed with significantly less effort and at the same time with a higher probability. Additionally, sales automation makes sure that they never miss a chance to close a deal because they are always automatically informed of what their clients are doing, whether it be by email or the CRM system.
  • Lead conversion is ensured with a transparent and reliable information from the acquisition phase. Sales teams can create offers and talks more independently, which greatly decreases the amount of coordination and negotiation loops by shortening the sales cycle. Even with cross- and upselling campaigns, it is possible to segment customers in a targeted manner and only launch offers or campaigns to contacts for whom the end result is guaranteed. Sales Automation, such as, templates, personalization tools, and segmentation possibilities not only speeds up repetitive operations, like making email lists or tracking offers, but also improves the quality of the outcomes.
  • The presence of incorrect data or missing customer information in CRM system can be a big obstacle for sale teams. Through real-time synchronization between the marketing automation and CRM system, for instance, sales automation helps to reduce the risk of errors in this situation. All data is updated simultaneously via bidirectional synchronization, regardless of whether it is data entry, updating and enriching client data, or maintaining a complete database. It is also possible to automatically check for and repair duplicates, incomplete data records, and invalid address entries. As a result, every department that interacts with customers has a consistent and up-to-date.

Sales are becoming more automated and digitalized, which boosts sales potential in a targeted way and can support the company’s growth. Additionally, Sales Automation provides several opportunities for expansion that is quick, effective, and seamless. Companies should therefore not wait any longer to digitize and automate their processes – the competition may already be doing it. Only those who act quickly and take their processes to the next level can be one step ahead of the competition.

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!.

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