Big Data: quais os desafios enfrentados pelas empresas?
Nenhuma organização pode funcionar sem dados atualmente. Com enormes quantidades de informações sendo geradas a cada segundo a partir de transações comerciais, números de vendas, registros de clientes e muito mais, os dados são o combustível que move as empresas atualmente. Todos esses dados são empilhados em um enorme conjunto de informações conhecido como Big Data.
No entanto, para que esses dados sejam realmente úteis, esses dados precisam ser estruturados e analisados. É a isso que o Big Data Analytics, o ramo da TI que se dedica a analisar esses dados e extrair informações úteis, se dedica.
Porém, apesar de estar se espalhando e ganhando popularidade, ainda existem alguns desafios que as empresas enfrentam ao aplicar o Big Data Analytics. No artigo de hoje, analisaremos mais de perto esses desafios e quais são as maneiras de superá-los. Acompanhe!
Desafio #1 — Compreender o Big Data
Muitas vezes, as empresas não sabem até mesmo o básico: o que o Big Data é, quais são seus benefícios, qual infraestrutura é necessária etc. O resultado é que as empresas podem acabar desperdiçando muito tempo e recursos com algo que não sabem utilizar a seu favor.
Compreender de maneira clara o que o Big Data significa para sua empresa é fundamental para que seu projeto não fracasse.
Solução
O Big Data, sendo uma grande mudança para uma empresa, deve ser aceito primeiro pela alta administração e depois ir descendo a escada. Uma boa dica para isso é realizar treinamentos e workshops que mostrem o valor dos dados e como eles podem ser utilizados.
Para ver a aceitação crescer ainda mais, a implementação e o uso da nova solução de Big Data precisam ser monitorados e controlados. No entanto, não exagere no controle, pois isso pode ter um efeito adverso.
Desafio #2 — Integrar diversas fontes de dados
Literalmente, tudo no mundo pode fazer parte dos dados. Então, você pode imaginar a possibilidade de todos os tipos de fontes que geram dados alinhados com as metas ou objetivos de uma empresa.
Isso inevitavelmente resulta em desafios de integração de Big Data quando se trata de combinar dados de fontes diferentes como páginas de mídia social, relatórios financeiros, documentos de funcionários, registros de clientes, apresentações, e-mails, etc. para criar relatórios perspicazes.
Solução
Frequentemente negligenciada, mas muito importante, a integração de dados desempenha um papel significativo no desenvolvimento de análises, relatórios e BI. Diversas ferramentas de integração e ETL estão disponíveis no mercado para essa finalidade. Algumas ferramentas de integração populares incluem o Microsoft SQL, QlikView, IBM InfoSphere, CloverDX e Oracle Data Service Integrator.
Veja mais >> Por que e quando utilizar o Big Data?
Desafio #3 — Escassez de pessoas qualificadas
A análise dos dados é importante para tornar útil essa quantidade volumosa de informações que está sendo produzida a cada minuto. Com o aumento exponencial dos dados, uma enorme demanda por cientistas e analistas de Big Data foi criada no mercado.
É importante para as organizações de negócios contratar um cientista de dados com habilidades variadas, pois o trabalho de um cientista de dados é multidisciplinar.
Outro grande desafio enfrentado pelas empresas é a escassez de profissionais que entendam de análise de Big Data. Há uma grande escassez de profissionais qualificados em comparação com a crescente necessidade urgente de extrair informações dos dados.
Solução
As empresas estão investindo mais dinheiro no recrutamento de profissionais qualificados. Mas elas também têm que oferecer programas de treinamento para a equipe existente para obter o máximo deles.
Outro passo importante dado pelas organizações é a compra de soluções de análise de dados que são movidas por inteligência artificial / aprendizado de máquina.
Essas ferramentas podem ser executadas por profissionais que não são especialistas em ciência de dados, mas possuem conhecimentos básicos. Esta etapa ajuda as empresas a economizar muito dinheiro com o recrutamento.
Desafio #4 — Garantir a segurança dos dados
Uma vez que as empresas descobrem como usar o Big Data, isso lhes traz uma ampla gama de possibilidades e oportunidades. No entanto, também envolve os riscos potenciais associados aos dados no que diz respeito à privacidade e à segurança.
As ferramentas de Big Data usadas para análise e armazenamento utilizam fontes díspares de dados. Isso acaba levando a um alto risco de exposição, tornando a empresa vulnerável. Assim, o aumento da quantidade volumosa de dados aumenta as preocupações com privacidade e segurança.
Solução
A precaução contra os possíveis desafios de segurança de Big Data é colocar a segurança em primeiro lugar. É particularmente importante na fase de concepção da arquitetura da sua solução. Algumas etapas tomadas para proteger os dados incluem:
- Criptografia de dados;
- Segregação de funções;
- Identidade e controle de acesso;
- Implementação de segurança de endpoint;
- Monitoramento de segurança em tempo real;
- Utilização de ferramentas de segurança de Big Data.
Desafio #5 — Controlar os gastos com Big Data
O gerenciamento de Big Data, desde a fase de adoção, exige muitos gastos. Por exemplo, se sua empresa optar por usar uma solução local, deve estar pronta para gastar dinheiro em novo hardware, eletricidade, novos recrutamentos, como desenvolvedores e administradores, e assim por diante.
Por outro lado, as organizações que utilizam uma solução baseada em nuvem vão gastar em áreas como contratação de novos funcionários (desenvolvedores e administradores), serviços em nuvem, desenvolvimento, e também cobrir os custos associados ao desenvolvimento, configuração, bem como manutenção dos frameworks necessários.
Em ambos os casos, as organizações devem deixar espaço para expansões futuras para evitar que o crescimento fique fora de controle e, por sua vez, se torne muito caro.
Solução
O que quer que economize o dinheiro da sua empresa depende de seus objetivos de negócios e necessidades tecnológicas específicas.
Por exemplo, as organizações que desejam flexibilidade geralmente se beneficiam de soluções de big data baseadas em nuvem. Por outro lado, as empresas cujos requisitos de segurança são extremamente rígidos preferem o local a qualquer dia.
As organizações também podem optar por soluções híbridas em que partes de seus dados são mantidas e processadas na nuvem, com a outra parte removida com segurança no local.
Como você pode ver, a maioria dos desafios analisados pode ser prevista e tratada se sua solução de Big Data tiver uma arquitetura decente, bem organizada e bem pensada.
Por isso, entre em contato com a Kron Digital agora mesmo e veja como podemos transformar a análise de Big Data na sua organização!
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