Leverage Data Science Consulting Services To Set Up Your Data Strategy For 2022

Mar 29, 2022
Data-Science-Consulting-Services

As the famous saying goes, data is nothing without strategy. The mere presence of data doesn’t add value to businesses. A data strategy is what turns data into value. The right amalgamation of tools and processes that define the management and analysis of data helps businesses take informed decisions.

In 2022, as we head into another year of the pandemic, it is imperative for organizations to have an accelerated strategy to optimally extract value from data. A report by Harvard Business Review says that organizations make use of less than 50% of their structured data in decision making.

Why is Data Strategy Important?

A well-thought-out data strategy improves your chances of making data-driven and evidence-based business decisions. It helps you understand your customers better, discover new relevant trends, develop new products, improve operations, and optimize on your data assets.

  • It helps you set out how you want to use your data in practice
  • Clarify data priorities
  • Set data goals in terms of the kind of data you need, source of data, storage etc

Therefore, every business, regardless of size or industry, needs a robust data strategy that details what your business wants to achieve and how data can help you get there.

Key Pillars of a Good Data Strategy

  • Data Ingestion

Data ingestion is the first step to a strong data strategy. It involves the transportation of data from one or more sources to a storage medium like a data warehouse, where it can be accessed and used by the organization. It is a critical technology that assists organizations in leveraging a large volume of data for decision-making.

There are two major ways to carry out data ingestion – real-time and batch. Real-time data ingestion collects and transfers data in real time using solutions that monitor transactions without interfering with the workload of databases. This proves to be essential in cases of time-sensitivity. On the other hand, a batch-based data ingestion collects and transfers data in scheduled intervals. This is useful in cases when organizations need to collect specific data points on a regular basis.

Addressing data ingestion aspects ensures maintenance of high data quality and better data-driven decisions. It also plays a crucial role in faster data delivery, scalability, and data transformation.

  • Data Storage

With data assets growing rapidly, organizations need to ensure that they have a strong storage management strategy in place. Business analytics has also led to regular sharing of large volumes of data, both internally and externally. Therefore, a data storage strategy should account for diversity of data sources, distribution od data users and size of the organization. It needs to provide ease of access and shareability.

A good data storage strategy ensures that any data created is available for future access by everyone without the need to duplicate it.

Consequently, a data strategy in the current business environment needs to go beyond data creation and also address data storage with equal importance.

  • Data Visualization

Mastering the art and science of data visualization is a key aspect in deriving value from data. Therefore, data visualization capabilities form a major part of the overall data strategy. It helps determine the efficiency with which data assets can be leveraged. It also helps understand the level of insights that can be extracted from data assets.

Data reporting impacts business decision-making and therefore, a good data visualization strategy is key to driving various business projects. It helps transform data into useful insights to gain a comprehensive understanding of data assets and processes. A comprehensive data visualization strategy must consider three major aspects – business analytics, data science and user experience.

  • AI Data Governance

Traditional data governance strategies include policies and standards to enhance the use of information to achieve business goals. It also ensures the quality and security of data usage. But, with the rise of AI and big data, traditional data governance strategies are not sufficient. It has led to an increased need for a modern data governance strategy with effective quality controls.

There needs to be a shift in traditional approaches to data governance to incorporate the fast-paced technological transformation. Setting up AI data governance strategies can help businesses extract maximum quality from data in the most secure manner.

How Our Data Services Assist Businesses in Setting Up the Right Data Strategy for 2022?

An effective data strategy for 2022 is based on four pillars that include data ingestion, data storage, data visualization and AI data governance. 

As leading data science consulting service providers, we help your business become future-ready. We help you leverage big data analytics and artificial intelligence to optimize on useful insights from your data assets. With over eight years of experience, we help clients harness the power of data by implementing the right data strategy.

We cater to a wide range of clients from industries such as e-commerce, healthcare, and automobile. Our data science services have assisted clients in better decision-making and increased profitability. Our artificial intelligence solutions ensure quality control and increased process efficiencies. It also enables organizations to craft future-ready data strategies.

You can read more about our data science consulting process here. Please get in touch with us to know more about how we customize our services and processes as per your specific requirements.

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