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5 Data Problems Companies Still Face in 2021

With the amount of data being created increasing by approximately 40% every year, there’s no doubt that the data your business collects must be managed effectively for improving  business processes and sustainable growth. But as the volume of data grows, it’s no surprise that businesses continue to face challenges when it comes to effectively managing their data.

While new data solutions (such as a customer data platform) seem to appear all the time, many of the core data challenges businesses come to Temberton to solve today are often similar to those we’ve been solving for our clients for the past twenty-five years.

In this article, we will discuss the top 5 data challenges businesses face in 2021, as well as the some of the solutions that Temberton offers to help our clients overcome these ongoing data challenges.

1. Managing Data Growth

With organizations’ storage needs approximately doubling every two years, it comes as no surprise that managing this increasing volume of data is a critical challenge for businesses in 2021. Our clients often come to Temberton wondering how they can store, access, and analyze these growing data volumes in a sustainable and cost-efficient manner.

Why is data growing so fast for organizations?

There are a number of factors driving this data growth. Some of these include:

  • Growing diversity of data sources
  • Applications requiring more storage
  • Unstructured data
  • More customer data tracking
  • Regulatory requirements forcing organizations to retain more data
  • Organic business growth and acquisitions

With these factors in play, organizations must have a data storage solution in place that accounts for this scalability of data proactively while also driving down the associated costs of data storage.

Enter Cloud-Based Storage Solutions

To leave room for inevitable data growth, many businesses are turning to cloud-based storage solutions. Compared to traditional data storage, cloud storage offers inherent scalability as more storage can be added as needed. Cloud-based storage solutions also tend towards high response and processing times, as well as risk mitigation with backup and recovery. Cloud-based storage also tends to be a more cost-effective option as organizations only pay for the storage they currently need.

2. Managing Data Diversity

As previously discussed, the data organizations manage today comes from an increasing variety of internal and external sources and formats, from enterprise applications to social media channels to internal documents. The growing variety of data from external sources has led to a sharp increase in unstructured data.

In fact, the vast majority of today’s data (nearly 80%!) is unstructured and only continues to grow.

This increase in unstructured data leads to a number of challenges for businesses as they grapple with managing and analyzing said data efficiently.

With this in mind, it is crucial that businesses have a strategy in place to analyze their unstructured data in order to glean insights and ultimately guide key business decisions.

The challenge, however, is that the data analytics processes required to analyze unstructured data are often complex and time-consuming. So how can businesses ensure their unstructured data is being utilized efficiently and cost effectively?

High-Tech Solutions For Unstructured Data

Thankfully, today’s technologies have come a long way in helping organizations gain a better understanding of the unstructured data they possess. Artificial intelligence (AI) and machine learning (ML) technologies such as Internet of Things (IoT), Computer Vision, and Document Understanding are allowing organizations to better extract timely, valuable insights from unstructured data sources.

3. Data Hygiene Issues

Clients often come to us wondering how they can ensure the accuracy and quality of their data. Poor data hygiene is an ongoing challenge for businesses, and with a growing volume of data, this challenge will only increase in scale in 2021.

Some data hygiene issues include:

  • Duplicate records
  • Incomplete or outdated data
  • Non-standardized addresses
  • Malformed contact information

Bad data can lead to a number of problems for companies, from poor analytics to low customer satisfaction to compliance issues, all of which impact an organization’s bottom line. In fact, IBM estimated that bad data cost the US $3.1 trillion in 2016.

Best Practices For Data Hygiene

Taking steps to ensure better data hygiene processes will lead to higher data quality, ultimately improving analytics efforts for more efficient business processes and growth.

Some best practices for data hygiene include:

  • Performing consistent audits
  • Establishing standardization rules and constraints
  • Automating data cleansing
  • Updating data frequently and consistently

While no business has perfectly clean data, taking a proactive approach to data hygiene will save time and money in the long run for your organization.

4. Generating timely insights

 Many organizations come to Temberton because they are struggling to utilize their data and analytics effectively to gain the valuable insights necessary in guiding key business decisions, increasing productivity, and becoming more competitive.

Businesses must determine which data to analyze, how to analyze it and finally, how to use the insights gleaned to drive next steps and solve problems. 

Make no mistake: transforming data into valuable, timely, and actionable insights is no easy feat for any organization.

While good analysis leads to better decision-making abilities, bad analysis can lead to bad decisions that can cost a company money, customers, and reputation.

Temberton Analytics’ expertise helps businesses inspect, cleanse, transform and model data from a variety of sources in real time to set actionable insights at multiple organizational levels, ultimately building to a solution over time.

5. Data Compliance

With all this data, it’s now more critical than ever that organizations take the steps necessary to properly store and protect the sensitive data they possess.

Data compliance refers to the regulations that a business must follow in order to ensure the sensitive digital assets it possesses – including personally identifiable information and financial details – are guarded against lost, theft, and misuse.

Insights for professionals

Temberton specializes in implementing BI (business intelligence) and reporting solutions to make organizational data accessible and usable so analysts can extract real business value from their data in a more efficient and timely way.

These reporting tools also demonstrate compliance with various data privacy laws and regulations, including GDPR and CCPA, providing visibility into best data practices.

While data growth, diversity, hygiene and compliance are all ongoing challenges for businesses in 2021, no business has to go it alone.

Temberton’s expertise in data analytics, data management, and business support has helped transform raw data into business intelligence for over twenty-five years. Contact us today to learn more about how Temberton can help your business

Temberton Analytics, Inc.